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wacv_2025_b0f716002e | b0f716002e | wacv | 2,025 | Metric Compatible Training for Online Backfilling in Large-Scale Retrieval | Backfilling is the process of re-extracting all gallery embeddings from upgraded models in image retrieval systems. It inevitably spends a prohibitively large amount of computational cost and even entails the downtime of the service. Although backward-compatible learning sidesteps this challenge by tackling query-side ... | Seonguk Seo; Mustafa Gokhan Uzunbas; Bohyung Han; Sara Cao; Ser-Nam Lim | ECE & IPAI, Seoul National University; Meta; ECE & IPAI, Seoul National University + Meta; Meta; University of Central Florida | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Seo_Metric_Compatible_Training_for_Online_Backfilling_in_Large-Scale_Retrieval_WACV_2025_paper.html | 3 | 2301.03767 | Metric Compatible Training for Online Backfilling in Large-Scale Retrieval
Backfilling is the process of re-extracting all gallery embeddings from upgraded models in image retrieval systems. It inevitably spends a prohibitively large amount of computational cost and even entails the downtime of the service. Although ba... | [
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wacv_2025_c3c2ea451f | c3c2ea451f | wacv | 2,025 | MimicGait: A Model Agnostic Approach for Occluded Gait Recognition using Correlational Knowledge Distillation | Gait recognition is an important biometric technique over large distances. State-of-the-art gait recognition systems perform very well in controlled environments at close range. Recently there has been an increased interest in gait recognition in the wild prompted by the collection of outdoor more challenging datasets ... | Ayush Gupta; Rama Chellappa | Johns Hopkins University; Johns Hopkins University | Poster | main | https://github.com/Ayush-00/mimicgait | https://openaccess.thecvf.com/content/WACV2025/html/Gupta_MimicGait_A_Model_Agnostic_Approach_for_Occluded_Gait_Recognition_using_WACV_2025_paper.html | 0 | 2501.15666 | MimicGait: A Model Agnostic Approach for Occluded Gait Recognition using Correlational Knowledge Distillation
Gait recognition is an important biometric technique over large distances. State-of-the-art gait recognition systems perform very well in controlled environments at close range. Recently there has been an incre... | [
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wacv_2025_40f2127f95 | 40f2127f95 | wacv | 2,025 | Mind the Map! Accounting for Existing Maps When Estimating Online HDMaps from Sensors | While HDMaps are a crucial component of autonomous driving they are expensive to acquire and maintain. Estimating these maps from sensors therefore promises to significantly lighten costs. These estimations however overlook existing HDMaps with current methods at most geolocalizing low quality maps or considering a gen... | Rémy Sun; Li Yang; Diane Lingrand; Frederic Precioso | Universit ´e Cˆote d’Azur, Inria, CNRS, I3S, Maasai, Nice, France; Universit ´e Cˆote d’Azur, Inria, CNRS, I3S, Maasai, Nice, France; Universit ´e Cˆote d’Azur, Inria, CNRS, I3S, Maasai, Nice, France; Universit ´e Cˆote d’Azur, Inria, CNRS, I3S, Maasai, Nice, France | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Sun_Mind_the_Map_Accounting_for_Existing_Maps_When_Estimating_Online_WACV_2025_paper.html | 0 | Mind the Map! Accounting for Existing Maps When Estimating Online HDMaps from Sensors
While HDMaps are a crucial component of autonomous driving they are expensive to acquire and maintain. Estimating these maps from sensors therefore promises to significantly lighten costs. These estimations however overlook existing H... | [
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wacv_2025_cc9bb420f7 | cc9bb420f7 | wacv | 2,025 | Mind the Prompt: A Novel Benchmark for Prompt-Based Class-Agnostic Counting | Recently object counting has shifted towards class-agnostic counting (CAC) which counts instances of arbitrary object classes never seen during model training. With advancements in robust vision-and-language foundation models there is a growing interest in prompt-based CAC where object categories are specified using na... | Luca Ciampi; Nicola Messina; Matteo Pierucci; Giuseppe Amato; Marco Avvenuti; Fabrizio Falchi | CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; University of Pisa, Italy; CNR-ISTI, Pisa, Italy; University of Pisa, Italy; CNR-ISTI, Pisa, Italy | Poster | main | https://github.com/ciampluca/PrACo | https://openaccess.thecvf.com/content/WACV2025/html/Ciampi_Mind_the_Prompt_A_Novel_Benchmark_for_Prompt-Based_Class-Agnostic_Counting_WACV_2025_paper.html | 2 | 2409.15953 | Mind the Prompt: A Novel Benchmark for Prompt-Based Class-Agnostic Counting
Recently object counting has shifted towards class-agnostic counting (CAC) which counts instances of arbitrary object classes never seen during model training. With advancements in robust vision-and-language foundation models there is a growing... | [
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wacv_2025_dfd048130d | dfd048130d | wacv | 2,025 | MissionGNN: Hierarchical Multimodal GNN-Based Weakly Supervised Video Anomaly Recognition with Mission-Specific Knowledge Graph Generation | In the context of escalating safety concerns across various domains the tasks of Video Anomaly Detection (VAD) and Video Anomaly Recognition (VAR) have emerged as critically important for applications in intelligent surveillance evidence investigation violence alerting etc. These tasks aimed at identifying and classify... | Sanggeon Yun; Ryozo Masukawa; Minhyoung Na; Mohsen Imani | University of California, Irvine; University of California, Irvine; Kookmin University; University of California, Irvine | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yun_MissionGNN_Hierarchical_Multimodal_GNN-Based_Weakly_Supervised_Video_Anomaly_Recognition_with_WACV_2025_paper.html | 7 | 2406.18815 | MissionGNN: Hierarchical Multimodal GNN-Based Weakly Supervised Video Anomaly Recognition with Mission-Specific Knowledge Graph Generation
In the context of escalating safety concerns across various domains the tasks of Video Anomaly Detection (VAD) and Video Anomaly Recognition (VAR) have emerged as critically importa... | [
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wacv_2025_e3e83c23fb | e3e83c23fb | wacv | 2,025 | MixDiff: Mixing Natural and Synthetic Images for Robust Self-Supervised Representations | This paper introduces MixDiff a new self-supervised learning (SSL) pre-training framework that combines real and synthetic images. Unlike traditional SSL methods that predominantly use real images MixDiff uses a variant of Stable Diffusion to replace an augmented instance of a real image facilitating the learning of cr... | Reza Akbarian Bafghi; Nidhin Harilal; Maziar Raissi; Claire Monteleoni | University of Colorado, Boulder; University of Colorado, Boulder; University of Colorado, Boulder+INRIA, Paris; University of California, Riverside | Poster | main | https://github.com/cryptonymous9/mixing-ssl | https://openaccess.thecvf.com/content/WACV2025/html/Bafghi_MixDiff_Mixing_Natural_and_Synthetic_Images_for_Robust_Self-Supervised_Representations_WACV_2025_paper.html | 0 | 2406.12368 | MixDiff: Mixing Natural and Synthetic Images for Robust Self-Supervised Representations
This paper introduces MixDiff a new self-supervised learning (SSL) pre-training framework that combines real and synthetic images. Unlike traditional SSL methods that predominantly use real images MixDiff uses a variant of Stable Di... | [
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wacv_2025_cf0af5064b | cf0af5064b | wacv | 2,025 | Mixed Patch Visible-Infrared Modality Agnostic Object Detection | In real-world scenarios using multiple modalities like visible (RGB) and infrared (IR) can greatly improve the performance of a predictive task such as object detection (OD). Multimodal learning is a common way to leverage these modalities where multiple modality-specific encoders and a fusion module are used to improv... | Heitor R. Medeiros; David Latortue; Eric Granger; Marco Pedersoli | Laboratoire d’imagerie, de vision et d’intelligence artificielle (LIVIA) + International Laboratory on Learning Systems (ILLS) + Dept. of Systems Engineering, ETS Montreal, Canada; Laboratoire d’imagerie, de vision et d’intelligence artificielle (LIVIA) + International Laboratory on Learning Systems (ILLS) + Dept. of Sys... | Poster | main | https://github.com/heitorrapela/MiPa | https://openaccess.thecvf.com/content/WACV2025/html/Medeiros_Mixed_Patch_Visible-Infrared_Modality_Agnostic_Object_Detection_WACV_2025_paper.html | 0 | Mixed Patch Visible-Infrared Modality Agnostic Object Detection
In real-world scenarios using multiple modalities like visible (RGB) and infrared (IR) can greatly improve the performance of a predictive task such as object detection (OD). Multimodal learning is a common way to leverage these modalities where multiple m... | [
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wacv_2025_12da6b4778 | 12da6b4778 | wacv | 2,025 | MoRAG - Multi-Fusion Retrieval Augmented Generation for Human Motion | We introduce MoRAG a novel multi-part fusion based retrieval-augmented generation strategy for text-based human motion generation. The method enhances motion diffusion models by leveraging additional knowledge obtained through an improved motion retrieval process. By effectively prompting large language models (LLMs) w... | Sai Shashank Kalakonda; Shubh Maheshwari; Ravi Kiran Sarvadevabhatla | CVIT, IIIT Hyderabad; University of California San Diego; CVIT, IIIT Hyderabad | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kalakonda_MoRAG_-_Multi-Fusion_Retrieval_Augmented_Generation_for_Human_Motion_WACV_2025_paper.html | 1 | MoRAG - Multi-Fusion Retrieval Augmented Generation for Human Motion
We introduce MoRAG a novel multi-part fusion based retrieval-augmented generation strategy for text-based human motion generation. The method enhances motion diffusion models by leveraging additional knowledge obtained through an improved motion retri... | [
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wacv_2025_37226ba84e | 37226ba84e | wacv | 2,025 | Modality-Incremental Learning with Disjoint Relevance Mapping Networks for Image-Based Semantic Segmentation | In autonomous driving environment perception has significantly advanced with the utilization of deep learning techniques for diverse sensors such as cameras depth sensors or infrared sensors. The diversity in the sensor stack increases the safety and contributes to robustness against adverse weather and lighting condit... | Niharika Hegde; Shishir Muralidhara; René Schuster; Didier Stricker | RPTU – University of Kaiserslautern-Landau + DFKI – German Research Center for Artificial Intelligence; RPTU – University of Kaiserslautern-Landau + DFKI – German Research Center for Artificial Intelligence; RPTU – University of Kaiserslautern-Landau + DFKI – German Research Center for Artificial Intelligence; RPTU – U... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Hegde_Modality-Incremental_Learning_with_Disjoint_Relevance_Mapping_Networks_for_Image-Based_Semantic_WACV_2025_paper.html | 1 | 2411.17610 | Modality-Incremental Learning with Disjoint Relevance Mapping Networks for Image-Based Semantic Segmentation
In autonomous driving environment perception has significantly advanced with the utilization of deep learning techniques for diverse sensors such as cameras depth sensors or infrared sensors. The diversity in th... | [
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wacv_2025_f02d0d5af3 | f02d0d5af3 | wacv | 2,025 | Moment of Untruth: Dealing with Negative Queries in Video Moment Retrieval | Video Moment Retrieval is a common task to evaluate the performance of visual-language models - it involves localising start and end times of moments in videos from query sentences. The current task formulation assumes that the queried moment is present in the video resulting in false positive moment predictions when i... | Kevin Flanagan; Dima Damen; Michael Wray | University of Bristol; University of Bristol; University of Bristol | Poster | main | https://github.com/keflanagan/MomentofUntruth | https://openaccess.thecvf.com/content/WACV2025/html/Flanagan_Moment_of_Untruth_Dealing_with_Negative_Queries_in_Video_Moment_WACV_2025_paper.html | 0 | 2502.08544 | Moment of Untruth: Dealing with Negative Queries in Video Moment Retrieval
Video Moment Retrieval is a common task to evaluate the performance of visual-language models - it involves localising start and end times of moments in videos from query sentences. The current task formulation assumes that the queried moment is... | [
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wacv_2025_03447a5bad | 03447a5bad | wacv | 2,025 | MonoPP: Metric-Scaled Self-Supervised Monocular Depth Estimation by Planar-Parallax Geometry in Automotive Applications | Self-supervised monocular depth estimation (MDE) has gained popularity for obtaining depth predictions directly from videos. However these methods often produce scale-invariant results unless additional training signals are provided. Addressing this challenge we introduce a novel self-supervised metric-scaled MDE model... | Gasser Elazab; Torben Gräber; Michael Unterreiner; Olaf Hellwich | ;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Elazab_MonoPP_Metric-Scaled_Self-Supervised_Monocular_Depth_Estimation_by_Planar-Parallax_Geometry_in_WACV_2025_paper.html | 0 | MonoPP: Metric-Scaled Self-Supervised Monocular Depth Estimation by Planar-Parallax Geometry in Automotive Applications
Self-supervised monocular depth estimation (MDE) has gained popularity for obtaining depth predictions directly from videos. However these methods often produce scale-invariant results unless addition... | [
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wacv_2025_3f98b06f9c | 3f98b06f9c | wacv | 2,025 | MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training | In the diverse field of medical imaging automatic segmentation has numerous applications and must handle a wide variety of input domains such as different types of Computed Tomography (CT) scans and Magnetic Resonance (MR) images. This heterogeneity challenges automatic segmentation algorithms to maintain consistent pe... | Chengyin Li; Hui Zhu; Rafi Ibn Sultan; Hassan Bagher Ebadian; Prashant Khanduri; Chetty Indrin; Kundan Thind; Dongxiao Zhu | Wayne State University+Henry Ford Health; Wayne State University; Wayne State University; Henry Ford Health; Wayne State University; Cedars Sinai Medical Center; Henry Ford Health; Wayne State University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Li_MulModSeg_Enhancing_Unpaired_Multi-Modal_Medical_Image_Segmentation_with_Modality-Conditioned_Text_WACV_2025_paper.html | 3 | 2411.15576 | MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training
In the diverse field of medical imaging automatic segmentation has numerous applications and must handle a wide variety of input domains such as different types of Computed Tomography (... | [
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wacv_2025_f5a5c16c34 | f5a5c16c34 | wacv | 2,025 | Multi-Aperture Transformers for 3D (MAT3D) Segmentation of Clinical and Microscopic Images | 3D segmentation of biological structures is critical in biomedical imaging offering significant insights into structures and functions. This paper introduces a novel segmentation of biological images that couples Multi-Aperture representation with Transformers for 3D (MAT3D) segmentation. Our method integrates the glob... | Muhammad Sohaib; Siyavash Shabani; Sahar A. Mohammed; Garrett Winkelmaier; Bahram Parvin | 1Department of Electrical and Biomedical Engineering, University of Nevada, Reno, USA+2Pennington Cancer Institute; 1Department of Electrical and Biomedical Engineering, University of Nevada, Reno, USA+2Pennington Cancer Institute; 1Department of Electrical and Biomedical Engineering, University of Nevada, Reno, USA; 1... | Poster | main | https://github.com/sohaibcs1/MAT3D | https://openaccess.thecvf.com/content/WACV2025/html/Sohaib_Multi-Aperture_Transformers_for_3D_MAT3D_Segmentation_of_Clinical_and_Microscopic_WACV_2025_paper.html | 0 | Multi-Aperture Transformers for 3D (MAT3D) Segmentation of Clinical and Microscopic Images
3D segmentation of biological structures is critical in biomedical imaging offering significant insights into structures and functions. This paper introduces a novel segmentation of biological images that couples Multi-Aperture r... | [
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wacv_2025_b7539ea015 | b7539ea015 | wacv | 2,025 | Multi-Class Textual-Inversion Secretly Yields a Semantic-Agnostic Classifier | With the advent of large pre-trained vision-language models such as CLIP prompt learning methods aim to enhance the transferability of the CLIP model. They learn the prompt given few samples from the downstream task given the specific class names as prior knowledge which we term as semantic-aware classification. Howeve... | Kai Wang; Fei Yang; Bogdan Raducanu; Joost van de Weijer | Computer Vision Center + Universitat Autònoma de Barcelona, Spain; VCIP, College of Computer Science, Nankai University, China + Nankai International Advanced Research Institute (SHENZHEN· FUTIAN), China; Computer Vision Center + Universitat Autònoma de Barcelona, Spain; Computer Vision Center + Universitat Autònoma de... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Wang_Multi-Class_Textual-Inversion_Secretly_Yields_a_Semantic-Agnostic_Classifier_WACV_2025_paper.html | 2 | 2410.22317 | Multi-Class Textual-Inversion Secretly Yields a Semantic-Agnostic Classifier
With the advent of large pre-trained vision-language models such as CLIP prompt learning methods aim to enhance the transferability of the CLIP model. They learn the prompt given few samples from the downstream task given the specific class na... | [
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wacv_2025_6a34fd8e17 | 6a34fd8e17 | wacv | 2,025 | Multi-HexPlanes: A Lightweight Map Representation for Rendering and 3D Reconstruction | Creating maps of the world around us is paramount to many applications including those related to robotics such as navigation and inspection. Given the computational resource limitations typical of robotic platforms there is a pressing need for lightweight 3D representations that capture detailed texture and geometric ... | Jianhao Zheng; Gábor Valasek; Daniel Barath; Iro Armeni | Stanford University; ELTE; ETH Zurich; Stanford University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zheng_Multi-HexPlanes_A_Lightweight_Map_Representation_for_Rendering_and_3D_Reconstruction_WACV_2025_paper.html | 0 | Multi-HexPlanes: A Lightweight Map Representation for Rendering and 3D Reconstruction
Creating maps of the world around us is paramount to many applications including those related to robotics such as navigation and inspection. Given the computational resource limitations typical of robotic platforms there is a pressin... | [
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wacv_2025_9267556795 | 9267556795 | wacv | 2,025 | Multi-Label Continual Learning for the Medical Domain: A Novel Benchmark | Despite the critical importance of the medical domain in Deep Learning most of the research in this area solely focuses on training models in static environments. It is only in recent years that research has begun to address dynamic environments and tackle the Catastrophic Forgetting problem through Continual Learning ... | Marina Ceccon; Davide Dalle Pezze; Alessandro Fabris; Gian Antonio Susto | University of Padova, Padova, Italy; University of Padova, Padova, Italy; Max Planck Institute for Security and Privacy, Bochum, Germany; University of Padova, Padova, Italy | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ceccon_Multi-Label_Continual_Learning_for_the_Medical_Domain_A_Novel_Benchmark_WACV_2025_paper.html | 4 | 2404.06859 | Multi-Label Continual Learning for the Medical Domain: A Novel Benchmark
Despite the critical importance of the medical domain in Deep Learning most of the research in this area solely focuses on training models in static environments. It is only in recent years that research has begun to address dynamic environments a... | [
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wacv_2025_62678d429d | 62678d429d | wacv | 2,025 | Multi-Level Feature Distillation of Joint Teachers Trained on Distinct Image Datasets | We propose a novel teacher-student framework to distill knowledge from multiple teachers trained on distinct datasets. Each teacher is first trained from scratch on its own dataset. Then the teachers are combined into a joint architecture which fuses the features of all teachers at multiple representation levels. The j... | Adrian Iordache; Bogdan Alexe; Radu Tudor Ionescu | ;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Iordache_Multi-Level_Feature_Distillation_of_Joint_Teachers_Trained_on_Distinct_Image_WACV_2025_paper.html | 1 | 2410.22184 | Multi-Level Feature Distillation of Joint Teachers Trained on Distinct Image Datasets
We propose a novel teacher-student framework to distill knowledge from multiple teachers trained on distinct datasets. Each teacher is first trained from scratch on its own dataset. Then the teachers are combined into a joint architec... | [
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wacv_2025_51684cbb29 | 51684cbb29 | wacv | 2,025 | Multi-Modal Large Language Model with RAG Strategies in Soccer Commentary Generation | As a globally celebrated sport soccer has seen its appeal greatly amplified by engaging and vivid commentary. Recently Multi-Modal Large Language Models (MLLMs) have attracted attention in generating soccer commentaries due to their remarkable capacities of understanding different modalities of the input videos. Most o... | Xiang Li; Yangfan He; Shuaishuai Zu; Zhengyang Li; Tianyu Shi; Yiting Xie; Kevin Zhang | Southern University of Science and Technology; University of Minnesota-Twin Cities; KNQ.AI+Renmin University of China; KNQ.AI+Imperial College London; University of Toronto; KNQ.AI; KNQ.AI | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Li_Multi-Modal_Large_Language_Model_with_RAG_Strategies_in_Soccer_Commentary_WACV_2025_paper.html | 0 | Multi-Modal Large Language Model with RAG Strategies in Soccer Commentary Generation
As a globally celebrated sport soccer has seen its appeal greatly amplified by engaging and vivid commentary. Recently Multi-Modal Large Language Models (MLLMs) have attracted attention in generating soccer commentaries due to their re... | [
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wacv_2025_3a9a866ae9 | 3a9a866ae9 | wacv | 2,025 | Multi-Modal Large Language Models are Effective Vision Learners | Large language models (LLMs) pre-trained on vast amounts of text have shown remarkable abilities in understanding general knowledge and commonsense. Therefore it's desirable to leverage pre-trained LLM to help solve computer vision tasks. Previous works on multi-modal LLM mainly focus on the generation capability. In t... | Li Sun; Chaitanya Ahuja; Peng Chen; Matt D'Zmura; Kayhan Batmanghelich; Philip Bontrager | Boston University; Meta; Meta; Meta; Boston University; Meta | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Sun_Multi-Modal_Large_Language_Models_are_Effective_Vision_Learners_WACV_2025_paper.html | 0 | Multi-Modal Large Language Models are Effective Vision Learners
Large language models (LLMs) pre-trained on vast amounts of text have shown remarkable abilities in understanding general knowledge and commonsense. Therefore it's desirable to leverage pre-trained LLM to help solve computer vision tasks. Previous works on... | [
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wacv_2025_a6006328f1 | a6006328f1 | wacv | 2,025 | Multi-Resolution Guided 3D GANs for Medical Image Translation | Medical image translation is the process of converting from one imaging modality to another in order to reduce the need for multiple image acquisitions from the same patient. This can enhance the efficiency of treatment by reducing the time equipment and labor needed. In this paper we introduce a multi-resolution guide... | Juhyung Ha; Jong Sung Park; David Crandall; Eleftherios Garyfallidis; Xuhong Zhang | Indiana University Bloomington; Indiana University Bloomington; Indiana University Bloomington; Indiana University Bloomington; Indiana University Bloomington | Poster | main | github.com/juhha/3D-mADUNet | https://openaccess.thecvf.com/content/WACV2025/html/Ha_Multi-Resolution_Guided_3D_GANs_for_Medical_Image_Translation_WACV_2025_paper.html | 0 | 2412.00575 | Multi-Resolution Guided 3D GANs for Medical Image Translation
Medical image translation is the process of converting from one imaging modality to another in order to reduce the need for multiple image acquisitions from the same patient. This can enhance the efficiency of treatment by reducing the time equipment and lab... | [
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wacv_2025_3f621a27d8 | 3f621a27d8 | wacv | 2,025 | Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation | Prototypical part learning is emerging as a promising approach for making semantic segmentation interpretable. The model selects real patches seen during training as prototypes and constructs the dense prediction map based on the similarity between parts of the test image and the prototypes. This improves interpretabil... | Hugo Porta; Emanuele Dalsasso; Diego Marcos; Devis Tuia | ;;; | Poster | main | github.com/eceo-epfl/ScaleProtoSeg | https://openaccess.thecvf.com/content/WACV2025/html/Porta_Multi-Scale_Grouped_Prototypes_for_Interpretable_Semantic_Segmentation_WACV_2025_paper.html | 0 | 2409.09497 | Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation
Prototypical part learning is emerging as a promising approach for making semantic segmentation interpretable. The model selects real patches seen during training as prototypes and constructs the dense prediction map based on the similarity between ... | [
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wacv_2025_3472e927a0 | 3472e927a0 | wacv | 2,025 | Multi-Spectral Image Color Reproduction | From camera to screen researchers have developed a well-established system for capturing and reproducing the color experience of human eyes. In this study we aim to upgrade this process by transiting from conventional RGB to multi-spectral image (MSI) color reproduction. While MSI offers evident advantages in color mat... | Jiacheng Li; Chang Chen; Xue Hu; Fenglong Song; Youliang Yan; Zhiwei Xiong | University of Science and Technology of China; Huawei Noah’s Ark Lab; Huawei Noah’s Ark Lab; Huawei Noah’s Ark Lab; Huawei Noah’s Ark Lab; University of Science and Technology of China | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Li_Multi-Spectral_Image_Color_Reproduction_WACV_2025_paper.html | 0 | Multi-Spectral Image Color Reproduction
From camera to screen researchers have developed a well-established system for capturing and reproducing the color experience of human eyes. In this study we aim to upgrade this process by transiting from conventional RGB to multi-spectral image (MSI) color reproduction. While MS... | [
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wacv_2025_13f5c74daa | 13f5c74daa | wacv | 2,025 | Multi-Surrogate-Teacher Assistance for Representation Alignment in Fingerprint-Based Indoor Localization | Despite remarkable progress in knowledge transfer across visual and textual domains extending these achievements to indoor localization particularly for learning transferable representations among Received Signal Strength (RSS) fingerprint datasets remains a challenge. This is due to inherent discrepancies among these ... | Son Minh Nguyen; Linh Duy Tran; Duc Le; Paul Havinga | Department of Computer Science, University of Twente; Viettel AI, Viettel Group; Department of Computer Science, University of Twente; Department of Computer Science, University of Twente | Poster | main | https://github.com/Minh-Son-Nguyen/RSS_TL | https://openaccess.thecvf.com/content/WACV2025/html/Nguyen_Multi-Surrogate-Teacher_Assistance_for_Representation_Alignment_in_Fingerprint-Based_Indoor_Localization_WACV_2025_paper.html | 0 | 2412.12189 | Multi-Surrogate-Teacher Assistance for Representation Alignment in Fingerprint-Based Indoor Localization
Despite remarkable progress in knowledge transfer across visual and textual domains extending these achievements to indoor localization particularly for learning transferable representations among Received Signal St... | [
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wacv_2025_912e6802df | 912e6802df | wacv | 2,025 | Multi-Task Learning of Classification and Generation for Set-Structured Data | In this study we propose a multi-task learning model of classification and generation for set-structured data. The proposed model learns data generation and classification in a single neural network by integrating a classification layer into a variational autoencoder while maintaining permutation invariance and equivar... | Fumioki Sato; Hideaki Hayashi; Hajime Nagahara | Osaka University; Osaka University; Osaka University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Sato_Multi-Task_Learning_of_Classification_and_Generation_for_Set-Structured_Data_WACV_2025_paper.html | 0 | Multi-Task Learning of Classification and Generation for Set-Structured Data
In this study we propose a multi-task learning model of classification and generation for set-structured data. The proposed model learns data generation and classification in a single neural network by integrating a classification layer into a... | [
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wacv_2025_dc2512006b | dc2512006b | wacv | 2,025 | Multi-View Factorizing and Disentangling: A Novel Framework for Incomplete Multi-View Multi-Label Classification | Multi-view multi-label classification (MvMLC) has recently garnered significant research attention due to its wide range of real-world applications. However incompleteness in views and labels is a common challenge often resulting from data collection oversights and uncertainties in manual annotation. Furthermore the ta... | Wulin Xie; Lian Zhao; Jiang Long; Xiaohuan Lu; Bingyan Nie | Guizhou University; Guizhou University; Guizhou University; Guizhou University; Guizhou University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Xie_Multi-View_Factorizing_and_Disentangling_A_Novel_Framework_for_Incomplete_Multi-View_WACV_2025_paper.html | 5 | 2501.06524 | Multi-View Factorizing and Disentangling: A Novel Framework for Incomplete Multi-View Multi-Label Classification
Multi-view multi-label classification (MvMLC) has recently garnered significant research attention due to its wide range of real-world applications. However incompleteness in views and labels is a common cha... | [
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wacv_2025_3511438eec | 3511438eec | wacv | 2,025 | Multi-View Image Diffusion via Coordinate Noise and Fourier Attention | Recently text-to-image generation with diffusion models has made significant advancements in both higher fidelity and generalization capabilities compared to previous baselines. However generating holistic multi-view consistent images from prompts still remains an important and challenging task. To address this challen... | Justin Theiss; Norman Müller; Daeil Kim; Aayush Prakash | ;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Theiss_Multi-View_Image_Diffusion_via_Coordinate_Noise_and_Fourier_Attention_WACV_2025_paper.html | 0 | Multi-View Image Diffusion via Coordinate Noise and Fourier Attention
Recently text-to-image generation with diffusion models has made significant advancements in both higher fidelity and generalization capabilities compared to previous baselines. However generating holistic multi-view consistent images from prompts st... | [
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wacv_2025_38700e9a19 | 38700e9a19 | wacv | 2,025 | Multimodal Fusion Learning with Dual Attention for Medical Imaging | Multimodal fusion learning has shown significant promise in classifying various diseases such as skin cancer and brain tumors. However existing methods face three key limitations. First they often lack generalizability to other diagnosis tasks due to their focus on a particular disease. Second they do not fully leverag... | Joy Dhar; Nayyar Zaidi; Maryam Haghighat; Sudipta Roy; Puneet Goyal; Azadeh Alavi; Vikas Kumar | ;;;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Dhar_Multimodal_Fusion_Learning_with_Dual_Attention_for_Medical_Imaging_WACV_2025_paper.html | 4 | 2412.01248 | Multimodal Fusion Learning with Dual Attention for Medical Imaging
Multimodal fusion learning has shown significant promise in classifying various diseases such as skin cancer and brain tumors. However existing methods face three key limitations. First they often lack generalizability to other diagnosis tasks due to th... | [
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wacv_2025_ed7113ad68 | ed7113ad68 | wacv | 2,025 | Multimodal Interpretable Depression Analysis using Visual Physiological Audio and Textual Data | Motivated by depression's significant impact on global health this work proposes MultiDepNet a novel multimodal interpretable depression detection system integrating visual physiological audio and textual data. Through dedicated feature extraction methods (MTCNN for video TS-CAN for physiological ResNet-18 for audio an... | Puneet Kumar; Shreshtha Misra; Zhuhong Shao; Bin Zhu; Balasubramanian Raman; Xiaobai Li | University of Oulu, Finland; IIT Roorkee, India; Capital Normal Univ., China; Hangzhou City Univ., China; IIT Roorkee, India; Zhejiang University, China | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kumar_Multimodal_Interpretable_Depression_Analysis_using_Visual_Physiological_Audio_and_Textual_WACV_2025_paper.html | 0 | Multimodal Interpretable Depression Analysis using Visual Physiological Audio and Textual Data
Motivated by depression's significant impact on global health this work proposes MultiDepNet a novel multimodal interpretable depression detection system integrating visual physiological audio and textual data. Through dedica... | [
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wacv_2025_232baa3b91 | 232baa3b91 | wacv | 2,025 | Multispectral Object Detection Enhanced by Cross-Modal Information Complementary and Cosine Similarity Channel Resampling Modules | Images obtained from different modalities can effectively enhance the accuracy and reliability of the detection model by complementing specialized information from visible (RGB) and infrared (IR) images. However integrating information from multiple modalities faces the following challenges: 1) distinct characteristics... | Junbo Jang; Chanyeong Park; Heegwang Kim; Jiyoon Lee; Joonki Paik | Chung-Ang University, Republic of Korea; Chung-Ang University, Republic of Korea; Chung-Ang University, Republic of Korea; Chung-Ang University, Republic of Korea; Chung-Ang University, Republic of Korea | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Jang_Multispectral_Object_Detection_Enhanced_by_Cross-Modal_Information_Complementary_and_Cosine_WACV_2025_paper.html | 0 | Multispectral Object Detection Enhanced by Cross-Modal Information Complementary and Cosine Similarity Channel Resampling Modules
Images obtained from different modalities can effectively enhance the accuracy and reliability of the detection model by complementing specialized information from visible (RGB) and infrared... | [
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wacv_2025_b755a79805 | b755a79805 | wacv | 2,025 | My3DGen: A Scalable Personalized 3D Generative Model | In recent years generative 3D face models (e.g. EG3D) have been developed to tackle the problem of synthesizing photo-realistic faces. However these models are often unable to capture facial features unique to each individual highlighting the importance of personalization. Some prior works have shown promise in persona... | Luchao Qi; Jiaye Wu; Annie N. Wang; Shengze Wang; Roni Sengupta | The University of North Carolina at Chapel Hill, USA; The University of Maryland, USA; The University of North Carolina at Chapel Hill, USA; The University of North Carolina at Chapel Hill, USA; The University of North Carolina at Chapel Hill, USA | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Qi_My3DGen_A_Scalable_Personalized_3D_Generative_Model_WACV_2025_paper.html | 2 | 2307.05468 | My3DGen: A Scalable Personalized 3D Generative Model
In recent years generative 3D face models (e.g. EG3D) have been developed to tackle the problem of synthesizing photo-realistic faces. However these models are often unable to capture facial features unique to each individual highlighting the importance of personaliz... | [
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wacv_2025_39e9ead91e | 39e9ead91e | wacv | 2,025 | NAT: Learning to Attack Neurons for Enhanced Adversarial Transferability | The generation of transferable adversarial perturbations typically involves training a generator to maximize embedding separation between clean and adversarial images at a single mid-layer of a source model. In this work we build on this approach and introduce Neuron Attack for Transferability (NAT) a method designed t... | Krishna Kanth Nakka; Alexandre Alahi | VITA Lab, EPFL, Switzerland; VITA Lab, EPFL, Switzerland | Poster | main | https://krishnakanthnakka.github.io/NAT/ | https://openaccess.thecvf.com/content/WACV2025/html/Nakka_NAT_Learning_to_Attack_Neurons_for_Enhanced_Adversarial_Transferability_WACV_2025_paper.html | 0 | NAT: Learning to Attack Neurons for Enhanced Adversarial Transferability
The generation of transferable adversarial perturbations typically involves training a generator to maximize embedding separation between clean and adversarial images at a single mid-layer of a source model. In this work we build on this approach ... | [
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wacv_2025_3ee776bd65 | 3ee776bd65 | wacv | 2,025 | NCAP: Scene Text Image Super-Resolution with Non-CAtegorical Prior | Scene text image super-resolution (STISR) enhances the resolution and quality of low-resolution images. Unlike previous studies that treated scene text images as natural images recent methods using a text prior (TP) extracted from a pre-trained text recognizer have shown strong performance. However two major issues eme... | Dongwoo Park; Suk Pil Ko | THINKWARE Corporation, Republic of Korea; THINKWARE Corporation, Republic of Korea | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Park_NCAP_Scene_Text_Image_Super-Resolution_with_Non-CAtegorical_Prior_WACV_2025_paper.html | 0 | NCAP: Scene Text Image Super-Resolution with Non-CAtegorical Prior
Scene text image super-resolution (STISR) enhances the resolution and quality of low-resolution images. Unlike previous studies that treated scene text images as natural images recent methods using a text prior (TP) extracted from a pre-trained text rec... | [
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wacv_2025_9d381d1e8e | 9d381d1e8e | wacv | 2,025 | NCAdapt: Dynamic Adaptation with Domain-Specific Neural Cellular Automata for Continual Hippocampus Segmentation | Continual learning (CL) in medical imaging presents a unique challenge requiring models to adapt to new domains while retaining previously acquired knowledge. We introduce NCAdapt a Neural Cellular Automata (NCA) based method designed to address this challenge. NCAdapt features a domain-specific multi-head structure in... | Amin Ranem; John Orlando Kalkhof; Anirban Mukhopadhyay | Technical University of Darmstadt; Technical University of Darmstadt; Technical University of Darmstadt | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ranem_NCAdapt_Dynamic_Adaptation_with_Domain-Specific_Neural_Cellular_Automata_for_Continual_WACV_2025_paper.html | 0 | 2410.23368 | NCAdapt: Dynamic Adaptation with Domain-Specific Neural Cellular Automata for Continual Hippocampus Segmentation
Continual learning (CL) in medical imaging presents a unique challenge requiring models to adapt to new domains while retaining previously acquired knowledge. We introduce NCAdapt a Neural Cellular Automata ... | [
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wacv_2025_7e8c46c7f5 | 7e8c46c7f5 | wacv | 2,025 | NPL-MVPS: Neural Point-Light Multi-View Photometric Stereo | In this work we present a novel multi-view photometric stereo (MVPS) method. Like many works in 3D reconstruction we are leveraging neural shape representations and learnt renderers. However our work differs from the state-of-the-art multi-view PS methods such as PS-NeRF or Supernormal in that we explicitly leverage pe... | Fotios Logothetis; Ignas Budvytis; Roberto Cipolla | Toshiba Europe; Independent researcher; University of Cambridge | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Logothetis_NPL-MVPS_Neural_Point-Light_Multi-View_Photometric_Stereo_WACV_2025_paper.html | 2 | NPL-MVPS: Neural Point-Light Multi-View Photometric Stereo
In this work we present a novel multi-view photometric stereo (MVPS) method. Like many works in 3D reconstruction we are leveraging neural shape representations and learnt renderers. However our work differs from the state-of-the-art multi-view PS methods such ... | [
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wacv_2025_189f63a204 | 189f63a204 | wacv | 2,025 | NarrAD: Automatic Generation of Audio Descriptions for Movies with Rich Narrative Context | Audio Description (AD) is a narration designed to enhance accessibility for visually impaired individuals by conveying the key visual elements of a video. Thus automating AD generation for long-form videos such as movies and dramas provides high social value but is a challenging task. First AD must reflect the narrativ... | Jaehyeong Park; Junchel Ye; Seungkook Lee; Hyun W. Ka; Dongsu Han | KAIST, Republic of Korea; KAIST, Republic of Korea; KAIST, Republic of Korea; KAIST, Republic of Korea; KAIST, Republic of Korea | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Park_NarrAD_Automatic_Generation_of_Audio_Descriptions_for_Movies_with_Rich_WACV_2025_paper.html | 0 | NarrAD: Automatic Generation of Audio Descriptions for Movies with Rich Narrative Context
Audio Description (AD) is a narration designed to enhance accessibility for visually impaired individuals by conveying the key visual elements of a video. Thus automating AD generation for long-form videos such as movies and drama... | [
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wacv_2025_e007a699ae | e007a699ae | wacv | 2,025 | Navigating Heterogeneity and Privacy in One-Shot Federated Learning with Diffusion Models | Federated learning (FL) enables multiple clients to train models collectively while preserving data privacy. However FL faces challenges in terms of communication cost and data heterogeneity. One-shot federated learning has emerged as a solution by reducing communication rounds improving efficiency and providing better... | Matias Mendieta; Guangyu Sun; Chen Chen | Center for Research in Computer Vision, University of Central Florida, USA; Center for Research in Computer Vision, University of Central Florida, USA; Center for Research in Computer Vision, University of Central Florida, USA | Poster | main | https://github.com/mmendiet/FedDiff | https://openaccess.thecvf.com/content/WACV2025/html/Mendieta_Navigating_Heterogeneity_and_Privacy_in_One-Shot_Federated_Learning_with_Diffusion_WACV_2025_paper.html | 3 | 2405.01494 | Navigating Heterogeneity and Privacy in One-Shot Federated Learning with Diffusion Models
Federated learning (FL) enables multiple clients to train models collectively while preserving data privacy. However FL faces challenges in terms of communication cost and data heterogeneity. One-shot federated learning has emerge... | [
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wacv_2025_62f5866e88 | 62f5866e88 | wacv | 2,025 | NeRFs are Mirror Detectors: using Structural Similarity for Multi-View Mirror Scene Reconstruction with 3D Surface Primitives | While neural radiance fields (NeRF) led to a breakthrough in photorealistic novel view synthesis handling mirroring surfaces still denotes a particular challenge as they introduce severe inconsistencies in the scene representation. Previous attempts either focus on reconstructing single reflective objects or rely on st... | Leif Van Holland; Michael Weinmann; Jan U. Müller; Patrick Stotko; Reinhard Klein | University of Bonn; Delft University of Technology; University of Bonn; University of Bonn; University of Bonn | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Van_Holland_NeRFs_are_Mirror_Detectors_using_Structural_Similarity_for_Multi-View_Mirror_WACV_2025_paper.html | 0 | NeRFs are Mirror Detectors: using Structural Similarity for Multi-View Mirror Scene Reconstruction with 3D Surface Primitives
While neural radiance fields (NeRF) led to a breakthrough in photorealistic novel view synthesis handling mirroring surfaces still denotes a particular challenge as they introduce severe inconsi... | [
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wacv_2025_d62f1c2720 | d62f1c2720 | wacv | 2,025 | Needles & Haystacks: Dataset and Benchmark for Domain-Agnostic Image-Based Rigid Slice-to-Volume Registration | We address domain-agnostic slice-to-volume (S2V) registration the alignment of 2D sliced/tomographic images into 3D volumes without prior knowledge of structure shape or orientation. While S2V registration is well-studied in medical imaging which often relies on auxiliary information (e.g. landmarks segmentation masks ... | Anton Frolov; Florian Kleiner; Christiane Rößler; Volker Rodehorst | Bauhaus-Universität Weimar; Bauhaus-Universität Weimar; Bauhaus-Universität Weimar; Bauhaus-Universität Weimar | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Frolov_Needles__Haystacks_Dataset_and_Benchmark_for_Domain-Agnostic_Image-Based_Rigid_WACV_2025_paper.html | 0 | Needles & Haystacks: Dataset and Benchmark for Domain-Agnostic Image-Based Rigid Slice-to-Volume Registration
We address domain-agnostic slice-to-volume (S2V) registration the alignment of 2D sliced/tomographic images into 3D volumes without prior knowledge of structure shape or orientation. While S2V registration is w... | [
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wacv_2025_2d5658f057 | 2d5658f057 | wacv | 2,025 | Negative-Prompt Inversion: Fast Image Inversion for Editing with Text-Guided Diffusion Models | In image editing employing diffusion models it is crucial to preserve the reconstruction fidelity to the original image while changing its style. Although existing methods ensure reconstruction fidelity through optimization a drawback of these is the significant amount of time required for optimization. In this paper w... | Daiki Miyake; Akihiro Iohara; Yu Saito; Toshiyuki Tanaka | The University of Tokyo, Japan + DATAGRID Inc., Japan; DATAGRID Inc., Japan; DATAGRID Inc., Japan; Kyoto University, Japan | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Miyake_Negative-Prompt_Inversion_Fast_Image_Inversion_for_Editing_with_Text-Guided_Diffusion_WACV_2025_paper.html | 106 | 2305.16807 | Negative-Prompt Inversion: Fast Image Inversion for Editing with Text-Guided Diffusion Models
In image editing employing diffusion models it is crucial to preserve the reconstruction fidelity to the original image while changing its style. Although existing methods ensure reconstruction fidelity through optimization a ... | [
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wacv_2025_b17a04f0c9 | b17a04f0c9 | wacv | 2,025 | NestedMorph: Enhancing Deformable Medical Image Registration with Nested Attention Mechanisms | Deformable image registration is crucial for aligning medical images in a nonlinear fashion across different modalities allowing for precise spatial correspondence between varying anatomical structures. This paper presents NestedMorph a novel network utilizing a Nested Attention Fusion approach to improve intra-subject... | Gurucharan Marthi Krishna Kumar; Janine Mendola; Amir Shmuel | Montreal Neurological Institute, McGill University; Dept. of Ophthalmology, McGill University; Montreal Neurological Institute, McGill University | Poster | main | https://github.com/AS-Lab/Marthi-et-al-2024-NestedMorph-Deformable-Medical-Image-Registration | https://openaccess.thecvf.com/content/WACV2025/html/Kumar_NestedMorph_Enhancing_Deformable_Medical_Image_Registration_with_Nested_Attention_Mechanisms_WACV_2025_paper.html | 0 | 2410.02550 | NestedMorph: Enhancing Deformable Medical Image Registration with Nested Attention Mechanisms
Deformable image registration is crucial for aligning medical images in a nonlinear fashion across different modalities allowing for precise spatial correspondence between varying anatomical structures. This paper presents Nes... | [
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wacv_2025_ff5cb5009f | ff5cb5009f | wacv | 2,025 | NeuManifold: Neural Watertight Manifold Reconstruction with Efficient and High-Quality Rendering Support | While existing volumetric rendering approaches provide photorealistic results extracting high-quality meshes from optimized neural field representations is challenging. Conversely existing differentiable rasterization-based methods are typically sensitive to initialization and suffer from poor mesh rendering quality. I... | Xinyue Wei; Fanbo Xiang; Sai Bi; Anpei Chen; Kalyan Sunkavalli; Zexiang Xu; Hao Su | University of California San Diego; University of California San Diego; Adobe Research; ETH Zürich+University of Tübingen; Adobe Research; Adobe Research; University of California San Diego | Poster | main | https://sarahweiii.github.io/neumanifold/ | https://openaccess.thecvf.com/content/WACV2025/html/Wei_NeuManifold_Neural_Watertight_Manifold_Reconstruction_with_Efficient_and_High-Quality_Rendering_WACV_2025_paper.html | 15 | 2305.17134 | NeuManifold: Neural Watertight Manifold Reconstruction with Efficient and High-Quality Rendering Support
While existing volumetric rendering approaches provide photorealistic results extracting high-quality meshes from optimized neural field representations is challenging. Conversely existing differentiable rasterizati... | [
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wacv_2025_27998c5ea5 | 27998c5ea5 | wacv | 2,025 | Neural Graph Map: Dense Mapping with Efficient Loop Closure Integration | Neural field-based SLAM methods typically employ a single monolithic field as their scene representation. This prevents efficient incorporation of loop closure constraints and limits scalability. To address these shortcomings we propose a novel RGB-D neural mapping framework in which the scene is represented by a colle... | Leonard Bruns; Jun Zhang; Patric Jensfelt | KTH Royal Institute of Technology, Stockholm, Sweden; TU Graz, Graz, Austria; KTH Royal Institute of Technology, Stockholm, Sweden | Poster | main | https://github.com/KTH-RPL/neural_graph_mapping | https://openaccess.thecvf.com/content/WACV2025/html/Bruns_Neural_Graph_Map_Dense_Mapping_with_Efficient_Loop_Closure_Integration_WACV_2025_paper.html | 0 | Neural Graph Map: Dense Mapping with Efficient Loop Closure Integration
Neural field-based SLAM methods typically employ a single monolithic field as their scene representation. This prevents efficient incorporation of loop closure constraints and limits scalability. To address these shortcomings we propose a novel RGB... | [
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wacv_2025_c8a6b51715 | c8a6b51715 | wacv | 2,025 | Neural SDF for Shadow-Aware Unsupervised Structured Light | Among various active 3D measurement techniques Structured Light (SL) is one of the most popular method for its robustness and high accuracy. Ordinary SL system consists of a camera and a projector and by projecting a pre-defined pattern we can obtain pixel-to-pixel correspondences between the camera and the projector f... | Kazuto Ichimaru; Diego Thomas; Takafumi Iwaguchi; Hiroshi Kawasaki | ;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ichimaru_Neural_SDF_for_Shadow-Aware_Unsupervised_Structured_Light_WACV_2025_paper.html | 0 | Neural SDF for Shadow-Aware Unsupervised Structured Light
Among various active 3D measurement techniques Structured Light (SL) is one of the most popular method for its robustness and high accuracy. Ordinary SL system consists of a camera and a projector and by projecting a pre-defined pattern we can obtain pixel-to-pi... | [
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wacv_2025_7a8bb80720 | 7a8bb80720 | wacv | 2,025 | NeuroViG - Integrating Event Cameras for Resource-Efficient Video Grounding | Spatio-Temporal Video Grounding (STVG) - the task of identifying the target object in the field-of-view that the language instruction refers to - is a fundamental vision-language task. Current STVG approaches typically utilize feeds from an RGB camera that is assumed to be always-on and process the video frames using c... | Dulanga Weerakoon; Vigneshwaran Subbaraju; Joo Hwee Lim; Archan Misra | SMART Centre; A*STAR, Singapore; A*STAR, Singapore; Singapore Management University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Weerakoon_NeuroViG_-_Integrating_Event_Cameras_for_Resource-Efficient_Video_Grounding_WACV_2025_paper.html | 0 | NeuroViG - Integrating Event Cameras for Resource-Efficient Video Grounding
Spatio-Temporal Video Grounding (STVG) - the task of identifying the target object in the field-of-view that the language instruction refers to - is a fundamental vision-language task. Current STVG approaches typically utilize feeds from an RGB... | [
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wacv_2025_a7bf5b50fc | a7bf5b50fc | wacv | 2,025 | No Annotations for Object Detection in Art through Stable Diffusion | Object detection in art is a valuable tool for the digital humanities as it allows for faster identification of objects in artistic and historical images compared to humans. However annotating such images poses significant challenges due to the need for specialized domain expertise. We present NADA (no annotations for ... | Patrick Ramos; Nicolas Gonthier; Selina Khan; Yuta Nakashima; Noa Garcia | Osaka University; Univ Gustave Eiffel, ENSG, IGN, LASTIG, France; University of Amsterdam; Osaka University; Osaka University | Poster | main | https://github.com/patrick-john-ramos/nada | https://openaccess.thecvf.com/content/WACV2025/html/Ramos_No_Annotations_for_Object_Detection_in_Art_through_Stable_Diffusion_WACV_2025_paper.html | 0 | 2412.06286 | No Annotations for Object Detection in Art through Stable Diffusion
Object detection in art is a valuable tool for the digital humanities as it allows for faster identification of objects in artistic and historical images compared to humans. However annotating such images poses significant challenges due to the need fo... | [
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wacv_2025_1435ef1218 | 1435ef1218 | wacv | 2,025 | Noise-Aware Evaluation of Object Detectors | Supervised object detection requires annotated datasets for training and evaluation purposes. However human annotation of large datasets is error-prone and frequent mistakes are erroneous labels missing objects and imprecise bounding boxes. The main goals of this work are to quantify the extent of annotation noise in t... | Jeffri Murrugarra Llerena; Claudio R. Jung | Computer Science Department, Stony Brook University; Institute of Informatics, Federal University of Rio Grande do Sul | Poster | main | https://github.com/Artcs1/Error-Aware | https://openaccess.thecvf.com/content/WACV2025/html/Llerena_Noise-Aware_Evaluation_of_Object_Detectors_WACV_2025_paper.html | 0 | Noise-Aware Evaluation of Object Detectors
Supervised object detection requires annotated datasets for training and evaluation purposes. However human annotation of large datasets is error-prone and frequent mistakes are erroneous labels missing objects and imprecise bounding boxes. The main goals of this work are to q... | [
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wacv_2025_2458993a5a | 2458993a5a | wacv | 2,025 | Non-Cross Diffusion for Semantic Consistency | In diffusion models deviations from a straight generative flow are a common issue resulting in semantic inconsistencies and suboptimal generations. To address this challenge we introduce `Non-Cross Diffusion' an innovative approach in generative modeling for learning ordinary differential equation (ODE) models. Our met... | Ziyang Zheng; Ruiyuan Gao; Qiang Xu | The Chinese University of Hong Kong; The Chinese University of Hong Kong; The Chinese University of Hong Kong | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zheng_Non-Cross_Diffusion_for_Semantic_Consistency_WACV_2025_paper.html | 0 | 2312.00820 | Non-Cross Diffusion for Semantic Consistency
In diffusion models deviations from a straight generative flow are a common issue resulting in semantic inconsistencies and suboptimal generations. To address this challenge we introduce `Non-Cross Diffusion' an innovative approach in generative modeling for learning ordinar... | [
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wacv_2025_0299b8516a | 0299b8516a | wacv | 2,025 | Now You See Me: Context-Aware Automatic Audio Description | Audio Description (AD) plays a pivotal role as an application system aimed at guaranteeing accessibility in multimedia content which provides additional narrations at suitable intervals to describe visual elements catering specifically to the needs of visually impaired audiences. In this paper we introduce CA3D the pio... | Seon-Ho Lee; Jue Wang; David Fan; Zhikang Zhang; Linda Liu; Xiang Hao; Vimal Bhat; Xinyu Li | Korea University*; Amazon AGI; Meta FAIR†; Amazon AGI; Amazon Prime Video; Amazon Prime Video; Amazon Prime Video; Amazon AGI | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Lee_Now_You_See_Me_Context-Aware_Automatic_Audio_Description_WACV_2025_paper.html | 2 | Now You See Me: Context-Aware Automatic Audio Description
Audio Description (AD) plays a pivotal role as an application system aimed at guaranteeing accessibility in multimedia content which provides additional narrations at suitable intervals to describe visual elements catering specifically to the needs of visually i... | [
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wacv_2025_93996c1055 | 93996c1055 | wacv | 2,025 | OPTIMUS: Observing Persistent Transformations in Multi-Temporal Unlabeled Satellite-Data | In the face of pressing environmental issues in the 21st century monitoring surface changes on Earth is more important than ever. Large-scale remote sensing such as satellite imagery is an important tool for this task. However using supervised methods to detect changes is difficult because of the lack of satellite data... | Raymond Yu; Paul Han; Piper Wolters; Favyen Bastani | University of Washington; University of Washington; Allen Institute for AI; Allen Institute for AI | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yu_OPTIMUS_Observing_Persistent_Transformations_in_Multi-Temporal_Unlabeled_Satellite-Data_WACV_2025_paper.html | 0 | OPTIMUS: Observing Persistent Transformations in Multi-Temporal Unlabeled Satellite-Data
In the face of pressing environmental issues in the 21st century monitoring surface changes on Earth is more important than ever. Large-scale remote sensing such as satellite imagery is an important tool for this task. However usin... | [
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wacv_2025_3453b5064f | 3453b5064f | wacv | 2,025 | ORFormer: Occlusion-Robust Transformer for Accurate Facial Landmark Detection | Although facial landmark detection (FLD) has gained significant progress existing FLD methods still suffer from performance drops on partially non-visible faces such as faces with occlusions or under extreme lighting conditions or poses. To address this issue we introduce ORFormer a novel transformer-based method that ... | Jui-Che Chiang; Hou-Ning Hu; Bo-Syuan Hou; Chia-Yu Tseng; Yu-Lun Liu; Min-Hung Chen; Yen-Yu Lin | National Yang Ming Chiao Tung University; MediaTek Inc.; National Yang Ming Chiao Tung University; National Yang Ming Chiao Tung University; National Yang Ming Chiao Tung University; NVIDIA; National Yang Ming Chiao Tung University | Poster | main | https://ben0919.github.io/ORFormer | https://openaccess.thecvf.com/content/WACV2025/html/Chiang_ORFormer_Occlusion-Robust_Transformer_for_Accurate_Facial_Landmark_Detection_WACV_2025_paper.html | 0 | 2412.13174 | ORFormer: Occlusion-Robust Transformer for Accurate Facial Landmark Detection
Although facial landmark detection (FLD) has gained significant progress existing FLD methods still suffer from performance drops on partially non-visible faces such as faces with occlusions or under extreme lighting conditions or poses. To a... | [
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wacv_2025_34c7d49d00 | 34c7d49d00 | wacv | 2,025 | ORID: Organ-Regional Information Driven Framework for Radiology Report Generation | The objective of Radiology Report Generation (RRG) is to automatically generate coherent textual analyses of diseases based on radiological images thereby alleviating the workload of radiologists. Current AI-based methods for RRG primarily focus on modifications to the encoder-decoder model architecture. To advance the... | Tiancheng Gu; Kaicheng Yang; Xiang An; Ziyong Feng; Dongnan Liu; Weidong Cai | University of Sydney; DeepGlint; DeepGlint; DeepGlint; University of Sydney; University of Sydney+DeepGlint | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Gu_ORID_Organ-Regional_Information_Driven_Framework_for_Radiology_Report_Generation_WACV_2025_paper.html | 2 | 2411.13025 | ORID: Organ-Regional Information Driven Framework for Radiology Report Generation
The objective of Radiology Report Generation (RRG) is to automatically generate coherent textual analyses of diseases based on radiological images thereby alleviating the workload of radiologists. Current AI-based methods for RRG primaril... | [
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wacv_2025_b9f0427a0c | b9f0427a0c | wacv | 2,025 | OT-VP: Optimal Transport-Guided Visual Prompting for Test-Time Adaptation | Vision Transformers (ViTs) have demonstrated remarkable capabilities in learning representations but their performance is compromised when applied to unseen domains. Previous methods either engage in prompt learning during the training phase or modify model parameters at test time through entropy minimization. The form... | Yunbei Zhang; Akshay Mehra; Jihun Hamm | Tulane University; Tulane University; Tulane University | Poster | main | https://github.com/zybeich/OT-VP | https://openaccess.thecvf.com/content/WACV2025/html/Zhang_OT-VP_Optimal_Transport-Guided_Visual_Prompting_for_Test-Time_Adaptation_WACV_2025_paper.html | 2 | OT-VP: Optimal Transport-Guided Visual Prompting for Test-Time Adaptation
Vision Transformers (ViTs) have demonstrated remarkable capabilities in learning representations but their performance is compromised when applied to unseen domains. Previous methods either engage in prompt learning during the training phase or m... | [
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wacv_2025_b942855b52 | b942855b52 | wacv | 2,025 | OTCXR: Rethinking Self-Supervised Alignment using Optimal Transport for Chest X-ray Analysis | Self-supervised learning (SSL) has emerged as a promising technique for analyzing medical modalities such as X-rays due to its ability to learn without annotations. However conventional SSL methods face challenges in achieving semantic alignment and capturing subtle details which limits their ability to accurately repr... | Vandan Gorade; Azad Singh; Deepak Mishra | Northwestern University; Indian Institute of Technology Jodhpur; Indian Institute of Technology Jodhpur | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Gorade_OTCXR_Rethinking_Self-Supervised_Alignment_using_Optimal_Transport_for_Chest_X-ray_WACV_2025_paper.html | 0 | OTCXR: Rethinking Self-Supervised Alignment using Optimal Transport for Chest X-ray Analysis
Self-supervised learning (SSL) has emerged as a promising technique for analyzing medical modalities such as X-rays due to its ability to learn without annotations. However conventional SSL methods face challenges in achieving ... | [
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wacv_2025_9282da860f | 9282da860f | wacv | 2,025 | OccFlowNet: Occupancy Estimation via Differentiable Rendering and Occupancy Flow | Semantic occupancy has recently gained significant traction as a prominent 3D scene representation. However most existing camera-based methods rely on large and costly datasets with fine-grained 3D voxel labels for training which limits their practicality and scalability. Furthermore approaches in this domain lack the ... | Simon Boeder; Benjamin Risse | ; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Boeder_OccFlowNet_Occupancy_Estimation_via_Differentiable_Rendering_and_Occupancy_Flow_WACV_2025_paper.html | 0 | OccFlowNet: Occupancy Estimation via Differentiable Rendering and Occupancy Flow
Semantic occupancy has recently gained significant traction as a prominent 3D scene representation. However most existing camera-based methods rely on large and costly datasets with fine-grained 3D voxel labels for training which limits th... | [
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wacv_2025_ee9a68946c | ee9a68946c | wacv | 2,025 | OccLoff: Learning Optimized Feature Fusion for 3D Occupancy Prediction | 3D semantic occupancy prediction is crucial for finely representing the surrounding environment which is essential for ensuring the safety in autonomous driving. Existing fusion-based occupancy methods typically involve performing a 2D-to-3D view transformation on image features followed by computationally intensive 3D... | Ji Zhang; Yiran Ding; Zixin Liu | Wuhan University; Wuhan University; Wuhan University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zhang_OccLoff_Learning_Optimized_Feature_Fusion_for_3D_Occupancy_Prediction_WACV_2025_paper.html | 2 | 2411.03696 | OccLoff: Learning Optimized Feature Fusion for 3D Occupancy Prediction
3D semantic occupancy prediction is crucial for finely representing the surrounding environment which is essential for ensuring the safety in autonomous driving. Existing fusion-based occupancy methods typically involve performing a 2D-to-3D view tr... | [
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wacv_2025_5b8bccc6ee | 5b8bccc6ee | wacv | 2,025 | OmniDiffusion: Reformulating 360 Monocular Depth Estimation using Semantic and Surface Normal Conditioned Diffusion | Depth estimation is the fundamental computer vision task for scene analysis. With the emergence of the deep learning era supervised monocular image depth estimation (MDE) became a popular choice for the task. Predominantly MDE methods utilize 360 images as ideal input due to their comprehensive field of view scene cont... | Payal Mohadikar; Ye Duan | University of Missouri, Missouri, USA; Clemson University, South Carolina, USA | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Mohadikar_OmniDiffusion_Reformulating_360_Monocular_Depth_Estimation_using_Semantic_and_Surface_WACV_2025_paper.html | 0 | OmniDiffusion: Reformulating 360 Monocular Depth Estimation using Semantic and Surface Normal Conditioned Diffusion
Depth estimation is the fundamental computer vision task for scene analysis. With the emergence of the deep learning era supervised monocular image depth estimation (MDE) became a popular choice for the t... | [
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wacv_2025_a0d6df9fb9 | a0d6df9fb9 | wacv | 2,025 | OmniGS: Fast Radiance Field Reconstruction using Omnidirectional Gaussian Splatting | Photorealistic reconstruction relying on 3D Gaussian Splatting has shown promising potential in various domains. However the current 3D Gaussian Splatting system only supports radiance field reconstruction using undistorted perspective images. In this paper we present OmniGS a novel omnidirectional Gaussian splatting s... | Longwei Li; Huajian Huang; Sai-Kit Yeung; Hui Cheng | Sun Yat-sen University; The Hong Kong University of Science and Technology; The Hong Kong University of Science and Technology; Sun Yat-sen University | Poster | main | https://github.com/liquorleaf/OmniGS | https://openaccess.thecvf.com/content/WACV2025/html/Li_OmniGS_Fast_Radiance_Field_Reconstruction_using_Omnidirectional_Gaussian_Splatting_WACV_2025_paper.html | 2 | 2404.03202 | OmniGS: Fast Radiance Field Reconstruction using Omnidirectional Gaussian Splatting
Photorealistic reconstruction relying on 3D Gaussian Splatting has shown promising potential in various domains. However the current 3D Gaussian Splatting system only supports radiance field reconstruction using undistorted perspective ... | [
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wacv_2025_b89dcee1e1 | b89dcee1e1 | wacv | 2,025 | On Explaining Knowledge Distillation: Measuring and Visualising the Knowledge Transfer Process | Knowledge distillation (KD) remains challenging due to the opaque nature of the knowledge transfer process from a Teacher to a Student making it difficult to address certain issues related to KD. To address this we proposed UniCAM a novel gradient-based visual explanation method which effectively interprets the knowled... | Gereziher Adhane; Mohammad Mahdi Dehshibi; Dennis Vetter; David Masip; Gemma Roig | Universitat Oberta de Catalunya; Universidad Carlos III de Madrid; Goethe University Frankfurt; Universitat Oberta de Catalunya; Goethe University Frankfurt | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Adhane_On_Explaining_Knowledge_Distillation_Measuring_and_Visualising_the_Knowledge_Transfer_WACV_2025_paper.html | 0 | 2412.13943 | On Explaining Knowledge Distillation: Measuring and Visualising the Knowledge Transfer Process
Knowledge distillation (KD) remains challenging due to the opaque nature of the knowledge transfer process from a Teacher to a Student making it difficult to address certain issues related to KD. To address this we proposed U... | [
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wacv_2025_b8e15f58f7 | b8e15f58f7 | wacv | 2,025 | On Neural BRDFs: A Thorough Comparison of State-of-the-Art Approaches | The bidirectional reflectance distribution function (BRDF) is an essential tool to capture the complex interaction of light and matter. Recently several works have employed neural methods for BRDF modeling following various strategies ranging from utilizing existing parametric models to purely neural parametrizations. ... | Florian Hofherr; Bjoern Haefner; Daniel Cremers | Technical University of Munich + Munich Center for Machine Learning + NVIDIA; Technical University of Munich + Munich Center for Machine Learning + NVIDIA; Technical University of Munich + Munich Center for Machine Learning | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Hofherr_On_Neural_BRDFs_A_Thorough_Comparison_of_State-of-the-Art_Approaches_WACV_2025_paper.html | 0 | On Neural BRDFs: A Thorough Comparison of State-of-the-Art Approaches
The bidirectional reflectance distribution function (BRDF) is an essential tool to capture the complex interaction of light and matter. Recently several works have employed neural methods for BRDF modeling following various strategies ranging from ut... | [
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wacv_2025_2a95a3f18d | 2a95a3f18d | wacv | 2,025 | On Which Data Distribution (Synthetic or Real) We Should Rely for Soft Biometric Classification | Identification of gender is critical not only for human-computer interaction but also for scrutinizing the search space in which an identity needs to be determined. Traditionally "real" facial images are employed for gender identification by computer vision algorithms. Due to the tremendous rise of privacy and advancem... | Manju R. A; Atul Kumar; Akshay Agarwal | Trustworthy BiometraVision Lab, IISER Bhopal; Trustworthy BiometraVision Lab, IISER Bhopal; Trustworthy BiometraVision Lab, IISER Bhopal | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/A_On_Which_Data_Distribution_Synthetic_or_Real_We_Should_Rely_WACV_2025_paper.html | 0 | On Which Data Distribution (Synthetic or Real) We Should Rely for Soft Biometric Classification
Identification of gender is critical not only for human-computer interaction but also for scrutinizing the search space in which an identity needs to be determined. Traditionally "real" facial images are employed for gender ... | [
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wacv_2025_c10d910d48 | c10d910d48 | wacv | 2,025 | On the Importance of Dual-Space Augmentation for Domain Generalized Object Detection | The distribution gap between training data and real-world data often causes significant performance drops in networks trained via naive supervised learning. To address this domain generalization methods have been developed to gain robust performance in unseen domains. In this paper we propose a single-domain generalize... | Hayoung Park; Choongsang Cho; Guisik Kim | Korea Electronics Technology Institute (KETI); Korea Electronics Technology Institute (KETI); Korea Electronics Technology Institute (KETI) | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Park_On_the_Importance_of_Dual-Space_Augmentation_for_Domain_Generalized_Object_WACV_2025_paper.html | 0 | On the Importance of Dual-Space Augmentation for Domain Generalized Object Detection
The distribution gap between training data and real-world data often causes significant performance drops in networks trained via naive supervised learning. To address this domain generalization methods have been developed to gain robu... | [
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wacv_2025_481ab6650d | 481ab6650d | wacv | 2,025 | On-the-Fly Object-aware Representative Point Selection in Point Cloud | Point clouds are essential for object modeling and play a critical role in assisting driving tasks for autonomous vehicles (AVs). However the significant volume of data generated by AVs creates challenges for storage bandwidth and processing cost. To tackle these challenges we propose a representative point selection f... | Xiaoyu Zhang; Ziwei Wang; Hai Dong; Zhifeng Bao; Jiajun Liu | RMIT University; CSIRO; RMIT University; RMIT University; CSIRO | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zhang_On-the-Fly_Object-aware_Representative_Point_Selection_in_Point_Cloud_WACV_2025_paper.html | 0 | On-the-Fly Object-aware Representative Point Selection in Point Cloud
Point clouds are essential for object modeling and play a critical role in assisting driving tasks for autonomous vehicles (AVs). However the significant volume of data generated by AVs creates challenges for storage bandwidth and processing cost. To... | [
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wacv_2025_774c460e49 | 774c460e49 | wacv | 2,025 | One VLM to Keep it Learning: Generation and Balancing for Data-Free Continual Visual Question Answering | Vision-Language Models (VLMs) have shown significant promise in Visual Question Answering (VQA) tasks by leveraging web-scale multimodal datasets. However these models often struggle with continual learning due to catastrophic forgetting when adapting to new tasks. As an effective remedy to mitigate catastrophic forget... | Deepayan Das; Davide Talon; Massimiliano Mancini; Yiming Wang; Elisa Ricci | University of Trento; Fondazione Bruno Kessler; University of Trento; Fondazione Bruno Kessler; University of Trento+Fondazione Bruno Kessler | Poster | main | https://github.com/Deepayan137/GaB | https://openaccess.thecvf.com/content/WACV2025/html/Das_One_VLM_to_Keep_it_Learning_Generation_and_Balancing_for_WACV_2025_paper.html | 1 | 2411.02210 | One VLM to Keep it Learning: Generation and Balancing for Data-Free Continual Visual Question Answering
Vision-Language Models (VLMs) have shown significant promise in Visual Question Answering (VQA) tasks by leveraging web-scale multimodal datasets. However these models often struggle with continual learning due to ca... | [
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wacv_2025_c7f2f503aa | c7f2f503aa | wacv | 2,025 | Online-LoRA: Task-Free Online Continual Learning via Low Rank Adaptation | Catastrophic forgetting is a significant challenge in online continual learning (OCL) especially for non-stationary data streams that do not have well-defined task boundaries. This challenge is exacerbated by the memory constraints and privacy concerns inherent in rehearsal buffers. To tackle catastrophic forgetting in... | Xiwen Wei; Guihong Li; Radu Marculescu | The University of Texas at Austin; The University of Texas at Austin; The University of Texas at Austin | Poster | main | https://github.com/Christina200/Online-LoRA-official.git | https://openaccess.thecvf.com/content/WACV2025/html/Wei_Online-LoRA_Task-Free_Online_Continual_Learning_via_Low_Rank_Adaptation_WACV_2025_paper.html | 4 | Online-LoRA: Task-Free Online Continual Learning via Low Rank Adaptation
Catastrophic forgetting is a significant challenge in online continual learning (OCL) especially for non-stationary data streams that do not have well-defined task boundaries. This challenge is exacerbated by the memory constraints and privacy con... | [
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wacv_2025_4ddcc4a0e8 | 4ddcc4a0e8 | wacv | 2,025 | OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics | Pose estimation has promised to impact healthcare by enabling more practical methods to quantify nuances of human movement and biomechanics. However despite the inherent connection between pose estimation and biomechanics these disciplines have largely remained disparate. For example most current pose estimation benchm... | Yoni Gozlan; Antoine Falisse; Scott Uhlrich; Anthony Gatti; Michael Black; Jennifer Hicks; Scott Delp; Akshay Chaudhari | Stanford University; Stanford University; Stanford University; Stanford University; Max Planck Institute for Intelligent Systems; Stanford University; Stanford University; Stanford University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Gozlan_OpenCapBench_A_Benchmark_to_Bridge_Pose_Estimation_and_Biomechanics_WACV_2025_paper.html | 6 | 2406.09788 | OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics
Pose estimation has promised to impact healthcare by enabling more practical methods to quantify nuances of human movement and biomechanics. However despite the inherent connection between pose estimation and biomechanics these disciplines have largel... | [
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wacv_2025_7dbb8b6ad8 | 7dbb8b6ad8 | wacv | 2,025 | OpenCity3D: What do Vision-Language Models Know About Urban Environments? | The rise of 2D vision-language models (VLMs) has enabled new possibilities for language-driven 3D scene understanding tasks. Existing works focus on indoor scenes or autonomous driving scenarios and typically validate against a pre-defined set of semantic object classes. In this work we analyze the capabilities of visi... | Valentin Bieri; Marco Zamboni; Nicolas Samuel Blumer; Qingxuan Chen; Francis Engelmann | ETH Zürich; ETH Zürich; ETH Zürich+University of Zurich; ETH Zürich+University of Zurich; ETH Zürich+Stanford University | Poster | main | https://github.com/opencity3d | https://openaccess.thecvf.com/content/WACV2025/html/Bieri_OpenCity3D_What_do_Vision-Language_Models_Know_About_Urban_Environments_WACV_2025_paper.html | 1 | OpenCity3D: What do Vision-Language Models Know About Urban Environments?
The rise of 2D vision-language models (VLMs) has enabled new possibilities for language-driven 3D scene understanding tasks. Existing works focus on indoor scenes or autonomous driving scenarios and typically validate against a pre-defined set of... | [
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wacv_2025_da948ed3dd | da948ed3dd | wacv | 2,025 | Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization | Multi-Task Learning (MTL) involves the concurrent training of multiple tasks offering notable advantages for dense prediction tasks in computer vision. MTL not only reduces training and inference time as opposed to having multiple single-task models but also enhances task accuracy through the interaction of multiple ta... | Maxime Fontana; Michael Spratling; Miaojing Shi | Department of Informatics, King’s College London; Department of Behavioural and Cognitive Sciences, University of Luxembourg; College of Electronic and Information Engineering, Tongji University | Poster | main | https://github.com/Klodivio355/MT-CP | https://openaccess.thecvf.com/content/WACV2025/html/Fontana_Optimizing_Dense_Visual_Predictions_Through_Multi-Task_Coherence_and_Prioritization_WACV_2025_paper.html | 0 | 2412.03179 | Optimizing Dense Visual Predictions Through Multi-Task Coherence and Prioritization
Multi-Task Learning (MTL) involves the concurrent training of multiple tasks offering notable advantages for dense prediction tasks in computer vision. MTL not only reduces training and inference time as opposed to having multiple singl... | [
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wacv_2025_3cecadcd51 | 3cecadcd51 | wacv | 2,025 | Optimizing Neural Network Effectiveness via Non-Monotonicity Refinement | Activation functions play a crucial role in artificial neural networks by introducing non-linearities that enable networks to learn complex patterns in data. An appropriate choice of an activation function plays a crucial role in the training dynamics of a neural network which can boost network performance significantl... | Koushik Biswas; Amit Reza; Meghana Karri; Debesh Jha; Hongyi Pan; Nikhil Tomar; Aliza Subedi; Smriti Regmi; Ulas Bagci | ;;;;;;;; | Poster | main | https://github.com/koushik313/AMSU | https://openaccess.thecvf.com/content/WACV2025/html/Biswas_Optimizing_Neural_Network_Effectiveness_via_Non-Monotonicity_Refinement_WACV_2025_paper.html | 0 | Optimizing Neural Network Effectiveness via Non-Monotonicity Refinement
Activation functions play a crucial role in artificial neural networks by introducing non-linearities that enable networks to learn complex patterns in data. An appropriate choice of an activation function plays a crucial role in the training dynam... | [
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wacv_2025_5555b2e676 | 5555b2e676 | wacv | 2,025 | Optimizing Vision-Language Model for Road Crossing Intention Estimation | Identifying a pedestrian's intention to cross the road is crucial for autonomous driving as it alerts the system to stop or slow down. However determining crossing intention from video is challenging due to the need for extracting complex high-level semantics. This paper introduces ClipCross a novel classification fram... | Roy Uziel; Oded Bialer | General Motors, Technical Center Israel + Ben-Gurion University of the Negev; General Motors, Technical Center Israel | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Uziel_Optimizing_Vision-Language_Model_for_Road_Crossing_Intention_Estimation_WACV_2025_paper.html | 0 | Optimizing Vision-Language Model for Road Crossing Intention Estimation
Identifying a pedestrian's intention to cross the road is crucial for autonomous driving as it alerts the system to stop or slow down. However determining crossing intention from video is challenging due to the need for extracting complex high-leve... | [
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wacv_2025_a04bba180b | a04bba180b | wacv | 2,025 | Ordinal Multiple-Instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer | Patient-level diagnosis of severity in ulcerative colitis (UC) is common in clinical practice where the most severe score for a patient is typically recorded as the diagnosis result. However previous UC classification methods (i.e. image-level estimation) mainly assumed the input was a single image. Thus these methods ... | Kaito Shiku; Kazuya Nishimura; Daiki Suehiro; Kiyohito Tanaka; Ryoma Bise | Kyushu University; National Cancer Center Japan; Kyushu University; Kyoto Second Red Cross Hospital; Kyushu University | Poster | main | https://github.com/Shiku-Kaito/Ordinal-Multiple-instance-Learning-for-Ulcerative-Colitis-Severity-Estimation | https://openaccess.thecvf.com/content/WACV2025/html/Shiku_Ordinal_Multiple-Instance_Learning_for_Ulcerative_Colitis_Severity_Estimation_with_Selective_WACV_2025_paper.html | 0 | 2411.14750 | Ordinal Multiple-Instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer
Patient-level diagnosis of severity in ulcerative colitis (UC) is common in clinical practice where the most severe score for a patient is typically recorded as the diagnosis result. However previous UC c... | [
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wacv_2025_e7e3294c1b | e7e3294c1b | wacv | 2,025 | Oriented Cell Dataset: A Dataset and Benchmark for Oriented Cell Detection and Applications | This work presents a new public dataset for cell detection in bright-field microscopy images annotated with Oriented Bounding Boxes (OBBs) named Oriented Cell Dataset (OCD). Our dataset also contains a subset of images with five independent expert annotations which allows inter-annotation analysis to determine a suitab... | Lucas Kirsten; Angelo Angonezi; Jose Marques; Fernanda Oliveira; Juliano Faccioni; Camila Cassel; Débora de Sousa; Samlai Vedovatto; Guido Lenz; Claudio Jung | Federal University of Rio Grande do Sul, Brazil – Institute of Informatics; Federal University of Rio Grande do Sul, Brazil – Institute of Biosciences; Federal University of Rio Grande do Sul, Brazil – Institute of Informatics; Federal University of Rio Grande do Sul, Brazil – Institute of Biosciences; Federal Universi... | Poster | main | https://github.com/LucasKirsten/Deep-Cell-Tracking-EBB | https://openaccess.thecvf.com/content/WACV2025/html/Kirsten_Oriented_Cell_Dataset_A_Dataset_and_Benchmark_for_Oriented_Cell_WACV_2025_paper.html | 0 | Oriented Cell Dataset: A Dataset and Benchmark for Oriented Cell Detection and Applications
This work presents a new public dataset for cell detection in bright-field microscopy images annotated with Oriented Bounding Boxes (OBBs) named Oriented Cell Dataset (OCD). Our dataset also contains a subset of images with five... | [
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wacv_2025_19839217f5 | 19839217f5 | wacv | 2,025 | PACA: Prespective-Aware Cross-Attention Representation for Zero-Shot Scene Rearrangement | Scene rearrangement like table tidying is a challenging task in robotic manipulation due to the complexity of predicting diverse object arrangements. Web-scale trained generative models such as Stable Diffusion can aid by generating natural scenes as goals. To facilitate robot execution object-level representations mus... | Shutong Jin; Ruiyu Wang; Kuangyi Chen; Florian T. Pokorny | KTH Royal Institute of Technology; KTH Royal Institute of Technology; Graz University of Technology; KTH Royal Institute of Technology | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Jin_PACA_Prespective-Aware_Cross-Attention_Representation_for_Zero-Shot_Scene_Rearrangement_WACV_2025_paper.html | 0 | PACA: Prespective-Aware Cross-Attention Representation for Zero-Shot Scene Rearrangement
Scene rearrangement like table tidying is a challenging task in robotic manipulation due to the complexity of predicting diverse object arrangements. Web-scale trained generative models such as Stable Diffusion can aid by generatin... | [
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wacv_2025_9e834e008a | 9e834e008a | wacv | 2,025 | PALO: A Polyglot Large Multimodal Model for 5B People | In pursuit of more inclusive Vision-Language Models (VLMs) this study introduces a Large Multilingual Multimodal Model called PALO. PALO offers visual reasoning capabilities in 10 major languages including English Chinese Hindi Spanish French Arabic Bengali Russian Urdu and Japanese that span a total of 5B people (65%... | Hanoona Rasheed; Muhammad Maaz; Abdelrahman Shaker; Salman Khan; Hisham Cholakkal; Rao M. Anwer; Tim Baldwin; Michael Felsberg; Fahad S. Khan | Mohamed bin Zayed University of AI; Mohamed bin Zayed University of AI; Mohamed bin Zayed University of AI; Mohamed bin Zayed University of AI+Australian National University; Mohamed bin Zayed University of AI; Mohamed bin Zayed University of AI+Aalto University; Mohamed bin Zayed University of AI+The University of Mel... | Poster | main | https://github.com/mbzuai-oryx/PALO | https://openaccess.thecvf.com/content/WACV2025/html/Rasheed_PALO_A_Polyglot_Large_Multimodal_Model_for_5B_People_WACV_2025_paper.html | 16 | 2402.14818 | PALO: A Polyglot Large Multimodal Model for 5B People
In pursuit of more inclusive Vision-Language Models (VLMs) this study introduces a Large Multilingual Multimodal Model called PALO. PALO offers visual reasoning capabilities in 10 major languages including English Chinese Hindi Spanish French Arabic Bengali Russian ... | [
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wacv_2025_6e2b5ebf13 | 6e2b5ebf13 | wacv | 2,025 | PC-GZSL: Prior Correction for Generalized Zero Shot Learning | Generalized Zero Shot Learning (GZSL) aims at achieving a good accuracy on both seen and unseen classes by relying on the information acquired from auxiliary attributes. Existing approaches have devised many frameworks to make this knowledge transfer more efficient and informative. Despite their effectiveness on boosti... | S Divakar Bhat; Amit More; Mudit Soni; Bhuvan Aggarwal | ;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Bhat_PC-GZSL_Prior_Correction_for_Generalized_Zero_Shot_Learning_WACV_2025_paper.html | 0 | PC-GZSL: Prior Correction for Generalized Zero Shot Learning
Generalized Zero Shot Learning (GZSL) aims at achieving a good accuracy on both seen and unseen classes by relying on the information acquired from auxiliary attributes. Existing approaches have devised many frameworks to make this knowledge transfer more eff... | [
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wacv_2025_89537271ed | 89537271ed | wacv | 2,025 | PETALface: Parameter Efficient Transfer Learning for Low-Resolution Face Recognition | Pre-training on large-scale datasets and utilizing margin-based loss functions have been highly successful in training models for high-resolution face recognition. However these models struggle with low-resolution face datasets in which the faces lack the facial attributes necessary for distinguishing different faces. ... | Kartik Narayan; Nithin Gopalakrishnan Nair; Jennifer Xu; Rama Chellappa; Vishal M. Patel | Johns Hopkins University; Johns Hopkins University; Systems and Technology Research; Johns Hopkins University; Johns Hopkins University | Poster | main | https://kartik-3004.github.io/PETALface/ | https://openaccess.thecvf.com/content/WACV2025/html/Narayan_PETALface_Parameter_Efficient_Transfer_Learning_for_Low-Resolution_Face_Recognition_WACV_2025_paper.html | 2 | 2412.07771 | PETALface: Parameter Efficient Transfer Learning for Low-Resolution Face Recognition
Pre-training on large-scale datasets and utilizing margin-based loss functions have been highly successful in training models for high-resolution face recognition. However these models struggle with low-resolution face datasets in whic... | [
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wacv_2025_c0294366df | c0294366df | wacv | 2,025 | PGRID: Power Grid Reconstruction in Informal Developments using High-Resolution Aerial Imagery | As of 2023 a record 117 million people have been displaced worldwide more than double the number from a decade ago [22]. Of these 32 million are refugees under the UNHCR mandate with 8.7 million residing in refugee camps. A critical issue faced by these populations is the lack of access to electricity with 80% of the 8... | Simone Fobi Nsutezo; Amrita Gupta; Duncan Kebut; Seema Iyer; Luana Marotti; Rahul Dodhia; Juan M. Lavista Ferres; Anthony Ortiz | Microsoft AI for Good Research Lab; Microsoft AI for Good Research Lab; HOTOSM; USA for UNHCR; Microsoft AI for Good Research Lab; Microsoft AI for Good Research Lab; Microsoft AI for Good Research Lab; Microsoft AI for Good Research Lab | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Nsutezo_PGRID_Power_Grid_Reconstruction_in_Informal_Developments_using_High-Resolution_Aerial_WACV_2025_paper.html | 0 | 2412.07944 | PGRID: Power Grid Reconstruction in Informal Developments using High-Resolution Aerial Imagery
As of 2023 a record 117 million people have been displaced worldwide more than double the number from a decade ago [22]. Of these 32 million are refugees under the UNHCR mandate with 8.7 million residing in refugee camps. A c... | [
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wacv_2025_0e87746b04 | 0e87746b04 | wacv | 2,025 | PICASSO: A Feed-Forward Framework for Parametric Inference of CAD Sketches via Rendering Self-Supervision | This work introduces PICASSO a framework for the parameterization of 2D CAD sketches from hand-drawn and precise sketch images. PICASSO converts a given CAD sketch image into parametric primitives that can be seamlessly integrated into CAD software. Our framework leverages rendering self-supervision to enable the pre-t... | Ahmet Serdar Karadeniz; Dimitrios Mallis; Nesryne Mejri; Kseniya Cherenkova; Anis Kacem; Djamila Aouada | ;;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Karadeniz_PICASSO_A_Feed-Forward_Framework_for_Parametric_Inference_of_CAD_Sketches_WACV_2025_paper.html | 4 | 2407.13394 | PICASSO: A Feed-Forward Framework for Parametric Inference of CAD Sketches via Rendering Self-Supervision
This work introduces PICASSO a framework for the parameterization of 2D CAD sketches from hand-drawn and precise sketch images. PICASSO converts a given CAD sketch image into parametric primitives that can be seaml... | [
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wacv_2025_2dbdc6c74c | 2dbdc6c74c | wacv | 2,025 | PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplanar MRI Slices | Brain tumor detection in multiplane Magnetic Resonance Imaging (MRI) slices is a challenging task due to the various appearances and relationships in the structure of the multiplane images. In this paper we propose a new You Only Look Once (YOLO)-based detection model that incorporates Pretrained Knowledge (PK) called ... | Ming Kang; Fung Fung Ting; Raphael C.-W. Phan; Chee-Ming Ting | Monash University Malaysia Campus; Monash University Malaysia Campus; Monash University Malaysia Campus; Monash University Malaysia Campus | Poster | main | https://github.com/mkang315/PK-YOLO | https://openaccess.thecvf.com/content/WACV2025/html/Kang_PK-YOLO_Pretrained_Knowledge_Guided_YOLO_for_Brain_Tumor_Detection_in_WACV_2025_paper.html | 0 | PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplanar MRI Slices
Brain tumor detection in multiplane Magnetic Resonance Imaging (MRI) slices is a challenging task due to the various appearances and relationships in the structure of the multiplane images. In this paper we propose a new You O... | [
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wacv_2025_b53a7bc415 | b53a7bc415 | wacv | 2,025 | PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive Representation Learning | Recently the usage of Contrastive Representation Learning (CRL) as a pre-training technique improves the performance of learning with noisy labels (LNL) methods. However instead of pre-training when trivially combining CRL loss with LNL methods as an end-to-end framework the empirical experiments show severe degenerati... | Xiaoyu Liu; Beitong Zhou; Zuogong Yue; Cheng Cheng | Huazhong University of Science and Technology; Huazhong University of Science and Technology; Huazhong University of Science and Technology; Huazhong University of Science and Technology | Poster | main | https://github.com/lxysl/PLReMix | https://openaccess.thecvf.com/content/WACV2025/html/Liu_PLReMix_Combating_Noisy_Labels_with_Pseudo-Label_Relaxed_Contrastive_Representation_Learning_WACV_2025_paper.html | 3 | 2402.17589 | PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive Representation Learning
Recently the usage of Contrastive Representation Learning (CRL) as a pre-training technique improves the performance of learning with noisy labels (LNL) methods. However instead of pre-training when trivially combining CRL los... | [
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wacv_2025_4960e46890 | 4960e46890 | wacv | 2,025 | PRoGS: Progressive Rendering of Gaussian Splats | Over the past year 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However it can require a substantial amount of storage since each splat's individual data must be stored. While compression techniques offer a potential solution b... | Brent Zoomers; Maarten Wijnants; Ivan Molenaers; Joni Vanherck; Jeroen Put; Lode Jorissen; Nick Michiels | Hasselt University - Flanders Make - Digital Future Lab, Diepenbeek, Belgium; Hasselt University - Flanders Make - Digital Future Lab, Diepenbeek, Belgium; Hasselt University - Flanders Make - Digital Future Lab, Diepenbeek, Belgium; Hasselt University - Flanders Make - Digital Future Lab, Diepenbeek, Belgium; Hasselt ... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zoomers_PRoGS_Progressive_Rendering_of_Gaussian_Splats_WACV_2025_paper.html | 2 | 2409.01761 | PRoGS: Progressive Rendering of Gaussian Splats
Over the past year 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However it can require a substantial amount of storage since each splat's individual data must be stored. While com... | [
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wacv_2025_c561bb5141 | c561bb5141 | wacv | 2,025 | PTQ4VM: Post-Training Quantization for Visual Mamba | Visual Mamba is an approach that extends the selective space state model Mamba to vision tasks. It processes image tokens sequentially in a fixed order accumulating information to generate outputs. Despite its growing popularity for delivering high-quality outputs at a low computational cost across various tasks Visual... | Younghyun Cho; Changhun Lee; Seonggon Kim; Eunhyeok Park | Pohang University of Science and Technology (POSTECH), Republic of Korea; Pohang University of Science and Technology (POSTECH), Republic of Korea; Pohang University of Science and Technology (POSTECH), Republic of Korea; Pohang University of Science and Technology (POSTECH), Republic of Korea | Poster | main | https://github.com/YoungHyun197/ptq4vm | https://openaccess.thecvf.com/content/WACV2025/html/Cho_PTQ4VM_Post-Training_Quantization_for_Visual_Mamba_WACV_2025_paper.html | 1 | 2412.20386 | PTQ4VM: Post-Training Quantization for Visual Mamba
Visual Mamba is an approach that extends the selective space state model Mamba to vision tasks. It processes image tokens sequentially in a fixed order accumulating information to generate outputs. Despite its growing popularity for delivering high-quality outputs at ... | [
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wacv_2025_61fc261c06 | 61fc261c06 | wacv | 2,025 | PULSE: Physiological Understanding with Liquid Signal Extraction | The non-contact estimation of vital signs particularly heart rate from video data is a promising method for remote health monitoring. 3D convolutional layers are widely used for this task due to their ability to capture both spatial and temporal features. However traditional 3D convolutions while effective in many case... | Shahzad Ahmad; Sania Bano; Sachin Verma; Yogesh Singh Rawat; Sukalpa Chanda; Santosh Kumar Vipparthi; Subrahmanyam Murala | Østfold University College, Norway; Indian Institute of Technology Ropar, India; Norwegian University of Science and Technology, Norway; University of Central Florida, USA; Østfold University College, Norway; Indian Institute of Technology Ropar, India; Trinity College Dublin, Ireland | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ahmad_PULSE_Physiological_Understanding_with_Liquid_Signal_Extraction_WACV_2025_paper.html | 0 | PULSE: Physiological Understanding with Liquid Signal Extraction
The non-contact estimation of vital signs particularly heart rate from video data is a promising method for remote health monitoring. 3D convolutional layers are widely used for this task due to their ability to capture both spatial and temporal features.... | [
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wacv_2025_a8d3d38942 | a8d3d38942 | wacv | 2,025 | PV-VTT: A Privacy-Centric Dataset for Mission-Specific Anomaly Detection and Natural Language Interpretation | Video crime detection is a significant application of computer vision and artificial intelligence. However existing datasets primarily focus on detecting severe crimes by analyzing entire video clips often neglecting the precursor activities (i.e. privacy violations) that could potentially prevent these crimes. To addr... | Ryozo Masukawa; Sanggeon Yun; Yoshiki Yamaguchi; Mohsen Imani | University of California, Irvine; University of California, Irvine; Shibaura Institute of Technology; University of California, Irvine | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Masukawa_PV-VTT_A_Privacy-Centric_Dataset_for_Mission-Specific_Anomaly_Detection_and_Natural_WACV_2025_paper.html | 1 | PV-VTT: A Privacy-Centric Dataset for Mission-Specific Anomaly Detection and Natural Language Interpretation
Video crime detection is a significant application of computer vision and artificial intelligence. However existing datasets primarily focus on detecting severe crimes by analyzing entire video clips often negle... | [
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wacv_2025_63e6e4ec3c | 63e6e4ec3c | wacv | 2,025 | PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction | Recently representations based on polar coordinates have exhibited promising characteristics for 3D perceptual tasks. In addition to Cartesian-based methods representing surrounding spaces through polar grids offers a compelling alternative in these tasks. This approach is advantageous for its ability to represent larg... | Yujing Xue; Jiaxiang Liu; Jiawei Du; Joey Tianyi Zhou | NUS; Zhejiang University; A*STAR+NUS; A*STAR | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Xue_PVP_Polar_Representation_Boost_for_3D_Semantic_Occupancy_Prediction_WACV_2025_paper.html | 0 | 2412.07616 | PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction
Recently representations based on polar coordinates have exhibited promising characteristics for 3D perceptual tasks. In addition to Cartesian-based methods representing surrounding spaces through polar grids offers a compelling alternative in these t... | [
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wacv_2025_6217274982 | 6217274982 | wacv | 2,025 | PVT: An Implicit Surface Reconstruction Framework via Point Voxel Geometric-Aware Transformer | 3D surface reconstruction from unorganized point clouds is a fundamental task in visual computing with numerous applications in areas such as robotics virtual reality augmented reality and animation. To date many deep learning-based surface reconstruction methods have been proposed demonstrating great performance on ma... | Chuanmao Fan; Chenxi Zhao; Ye Duan | University of Missouri-Columbia; Clemson University; Clemson University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Fan_PVT_An_Implicit_Surface_Reconstruction_Framework_via_Point_Voxel_Geometric-Aware_WACV_2025_paper.html | 0 | PVT: An Implicit Surface Reconstruction Framework via Point Voxel Geometric-Aware Transformer
3D surface reconstruction from unorganized point clouds is a fundamental task in visual computing with numerous applications in areas such as robotics virtual reality augmented reality and animation. To date many deep learning... | [
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wacv_2025_3809071d21 | 3809071d21 | wacv | 2,025 | Paladin: Understanding Video Intentions in Political Advertisement Videos | In this paper we introduce a novel task for video understanding that focuses on detecting editing intentions in political advertisement videos. Political advertisement videos are edited with some intentions (e.g. "associating some candidates with negative emotions") of making people unthinkingly believe the messages in... | Hong Liu; Yuta Nakashima; Noboru Babaguchi | Osaka University, Japan; Osaka University, Japan + Fukui University of Technology, Japan; Osaka University, Japan + Fukui University of Technology, Japan | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Liu_Paladin_Understanding_Video_Intentions_in_Political_Advertisement_Videos_WACV_2025_paper.html | 0 | Paladin: Understanding Video Intentions in Political Advertisement Videos
In this paper we introduce a novel task for video understanding that focuses on detecting editing intentions in political advertisement videos. Political advertisement videos are edited with some intentions (e.g. "associating some candidates with... | [
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wacv_2025_e53da2272b | e53da2272b | wacv | 2,025 | Partial Filter-Sharing: Improved Parameter-Sharing Method for Single Image Super-Resolution Networks | Numerous deep learning techniques have been developed for Single Image Super-Resolution (SISR) leading to significant performance improvements. However these techniques have also resulted in a substantial increase in parameter size. As a result there is a growing interest in reducing network complexity for more practic... | Karam Park; Nam Ik Cho | Department of ECE, INMC, Seoul National University; Department of ECE, INMC, Seoul National University | Poster | main | https://github.com/saturnian77/Partial_filter-Sharing | https://openaccess.thecvf.com/content/WACV2025/html/Park_Partial_Filter-Sharing_Improved_Parameter-Sharing_Method_for_Single_Image_Super-Resolution_Networks_WACV_2025_paper.html | 0 | Partial Filter-Sharing: Improved Parameter-Sharing Method for Single Image Super-Resolution Networks
Numerous deep learning techniques have been developed for Single Image Super-Resolution (SISR) leading to significant performance improvements. However these techniques have also resulted in a substantial increase in pa... | [
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wacv_2025_bfe559696a | bfe559696a | wacv | 2,025 | Partial Texture VAE: Color and Texture Encoder for Rock Particle Images | We propose Partial Texture VAE (PT-VAE) for rock particle image analysis a variant of the variational autoencoder (VAE) specialized in encoding color and texture properties from arbitrarily sized and shaped unresized images containing invalid background pixels into the vectors with the same size. PT-VAE integrates part... | Tetsushi Yamada; Simone Di Santo | SLB Schlumberger-Doll Research, Cambridge, Massachusetts, USA; SLB Schlumberger Dhahran Carbonate Research, Dhahran, Saudi Arabia | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yamada_Partial_Texture_VAE_Color_and_Texture_Encoder_for_Rock_Particle_WACV_2025_paper.html | 0 | Partial Texture VAE: Color and Texture Encoder for Rock Particle Images
We propose Partial Texture VAE (PT-VAE) for rock particle image analysis a variant of the variational autoencoder (VAE) specialized in encoding color and texture properties from arbitrarily sized and shaped unresized images containing invalid backg... | [
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wacv_2025_7eec510e07 | 7eec510e07 | wacv | 2,025 | Patch Ranking: Token Pruning as Ranking Prediction for Efficient CLIP | Contrastive image-text pre-trained models such as CLIP have shown remarkable adaptability to downstream tasks. However they face challenges due to the high computational requirements of the Vision Transformer (ViT) backbone. Current strategies to boost ViT efficiency focus on pruning patch tokens but fall short in addr... | Cheng-En Wu; Jinhong Lin; Yu Hen Hu; Pedro Morgado | University of Wisconsin–Madison; University of Wisconsin–Madison; University of Wisconsin–Madison; University of Wisconsin–Madison | Poster | main | https://github.com/CEWu/PatchRanking | https://openaccess.thecvf.com/content/WACV2025/html/Wu_Patch_Ranking_Token_Pruning_as_Ranking_Prediction_for_Efficient_CLIP_WACV_2025_paper.html | 0 | Patch Ranking: Token Pruning as Ranking Prediction for Efficient CLIP
Contrastive image-text pre-trained models such as CLIP have shown remarkable adaptability to downstream tasks. However they face challenges due to the high computational requirements of the Vision Transformer (ViT) backbone. Current strategies to boo... | [
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wacv_2025_55fe188aa4 | 55fe188aa4 | wacv | 2,025 | PatchFinder: Leveraging Visual Language Models for Accurate Information Retrieval using Model Uncertainty | For decades corporations and governments have relied on scanned documents to record vast amounts of information. However extracting this information is a slow and tedious process due to the sheer volume and complexity of these records. The rise of Vision Language Models (VLMs) presents a way to efficiently and accurate... | Roman Colman; Minh Vu; Manish Bhattarai; Martin Ma; Hari Viswanathan; Daniel O'Malley; Javier Santos | ;;;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Colman_PatchFinder_Leveraging_Visual_Language_Models_for_Accurate_Information_Retrieval_using_WACV_2025_paper.html | 0 | 2412.02886 | PatchFinder: Leveraging Visual Language Models for Accurate Information Retrieval using Model Uncertainty
For decades corporations and governments have relied on scanned documents to record vast amounts of information. However extracting this information is a slow and tedious process due to the sheer volume and complex... | [
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wacv_2025_1fad4eedbc | 1fad4eedbc | wacv | 2,025 | Pay Attention to Your Neighbours: Training-Free Open-Vocabulary Semantic Segmentation | Despite the significant progress in deep learning for dense visual recognition problems such as semantic segmentation traditional methods are constrained by fixed class sets. Meanwhile vision-language foundation models such as CLIP have showcased remarkable effectiveness in numerous zero-shot image-level tasks owing to... | Sina Hajimiri; Ismail Ben Ayed; Jose Dolz | ´ETS Montreal; ´ETS Montreal; ´ETS Montreal | Poster | main | https://github.com/sinahmr/NACLIP | https://openaccess.thecvf.com/content/WACV2025/html/Hajimiri_Pay_Attention_to_Your_Neighbours_Training-Free_Open-Vocabulary_Semantic_Segmentation_WACV_2025_paper.html | 20 | 2404.08181 | Pay Attention to Your Neighbours: Training-Free Open-Vocabulary Semantic Segmentation
Despite the significant progress in deep learning for dense visual recognition problems such as semantic segmentation traditional methods are constrained by fixed class sets. Meanwhile vision-language foundation models such as CLIP ha... | [
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wacv_2025_6ca3e07efe | 6ca3e07efe | wacv | 2,025 | Per-Pixel Solution of Multispectral Photometric Stereo | Photometric Stereo (PS) estimates surface normals by analyzing images lit from different angles. Enhancing PS with spectral imaging known as multispectral photometric stereo (MPS) uses varying light source colors for simultaneous image capture. As in traditional PS obtaining a unique solution is challenging in MPS when... | Shin Ishihara; Imari Sato | ; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ishihara_Per-Pixel_Solution_of_Multispectral_Photometric_Stereo_WACV_2025_paper.html | 0 | Per-Pixel Solution of Multispectral Photometric Stereo
Photometric Stereo (PS) estimates surface normals by analyzing images lit from different angles. Enhancing PS with spectral imaging known as multispectral photometric stereo (MPS) uses varying light source colors for simultaneous image capture. As in traditional PS... | [
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wacv_2025_ed57674351 | ed57674351 | wacv | 2,025 | Perceive Query & Reason: Enhancing Video QA with Question-Guided Temporal Queries | Video Question Answering (Video QA) is a challenging video understanding task that requires models to comprehend entire videos identify the most relevant information based on contextual cues from a given question and reason accurately to provide answers. Recent advancements in Multimodal Large Language Models (MLLMs) h... | Roberto Amoroso; Gengyuan Zhang; Rajat Koner; Lorenzo Baraldi; Rita Cucchiara; Volker Tresp | LMU Munich+MCML; LMU Munich+MCML; LMU Munich; University of Modena and Reggio Emilia; University of Modena and Reggio Emilia+IIT-CNR; LMU Munich+MCML | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Amoroso_Perceive_Query__Reason_Enhancing_Video_QA_with_Question-Guided_Temporal_WACV_2025_paper.html | 1 | 2412.19304 | Perceive Query & Reason: Enhancing Video QA with Question-Guided Temporal Queries
Video Question Answering (Video QA) is a challenging video understanding task that requires models to comprehend entire videos identify the most relevant information based on contextual cues from a given question and reason accurately to ... | [
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wacv_2025_89e6d0e916 | 89e6d0e916 | wacv | 2,025 | Personalized Mixture of Experts for Multi-Site Medical Image Segmentation | The sharing of sensitive medical data among institutions presents a significant challenge due to strict privacy regulations the need for robust de-identification processes and the ethical imperative to protect patient confidentiality. Federated Learning (FL) addresses these challenges by enabling institutions to collab... | Md Motiur Rahman; Mohamed Trabelsi; Huseyin Uzunalioglu; Aidan Boyd | Nokia Bell Labs; Nokia Bell Labs; Nokia Bell Labs; Nokia Bell Labs | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Rahman_Personalized_Mixture_of_Experts_for_Multi-Site_Medical_Image_Segmentation_WACV_2025_paper.html | 0 | Personalized Mixture of Experts for Multi-Site Medical Image Segmentation
The sharing of sensitive medical data among institutions presents a significant challenge due to strict privacy regulations the need for robust de-identification processes and the ethical imperative to protect patient confidentiality. Federated L... | [
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wacv_2025_4978a57c82 | 4978a57c82 | wacv | 2,025 | Phaseformer: Phase-Based Attention Mechanism for Underwater Image Restoration and Beyond | Quality degradation is observed in underwater images due to the effects of light refraction and absorption by water leading to issues like color cast haziness and limited visibility. This degradation negatively affects the performance of autonomous underwater vehicles used in marine applications. To address these chall... | Raqib Khan; Anshul Negi; Ashutosh Kulkarni; Shruti S. Phutke; Santosh Kumar Vipparthi; Subrahmanyam Murala | Trinity College Dublin, Ireland; Indian Institute of Technology Ropar, India; Indian Institute of Technology Ropar, India; Indian Institute of Technology Ropar, India; Indian Institute of Technology Ropar, India; Trinity College Dublin, Ireland | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Khan_Phaseformer_Phase-Based_Attention_Mechanism_for_Underwater_Image_Restoration_and_Beyond_WACV_2025_paper.html | 1 | 2412.01456 | Phaseformer: Phase-Based Attention Mechanism for Underwater Image Restoration and Beyond
Quality degradation is observed in underwater images due to the effects of light refraction and absorption by water leading to issues like color cast haziness and limited visibility. This degradation negatively affects the performa... | [
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wacv_2025_6db3fa4366 | 6db3fa4366 | wacv | 2,025 | Physiology-Aware PolySnake for Coronary Vessel Segmentation | Coronary artery disease (CAD) is a significant health risk that requires early detection for effective treatment. While recent advances in deep learning have shown promise in automating CAD detection from coronary computed tomography angiography (CCTA) images the accurate segmentation of coronary vessels remains a chal... | Yizhe Ruan; Lin Gu; Yusuke Kurose; Junichi Iho; Youji Tokunaga; Makoto Horie; Yusaku Hayashi; Keisuke Nishizawa; Yasushi Koyama; Tatsuya Harada | The University of Tokyo + RIKEN Center for Advanced Intelligence Project; RIKEN Center for Advanced Intelligence Project + The University of Tokyo; The University of Tokyo + RIKEN Center for Advanced Intelligence Project; Sakurabashi Watanabe Advanced Healthcare Hospital; Sakurabashi Watanabe Advanced Healthcare Hospit... | Poster | main | https://github.com/opensourcetorch/Physiology-aware-PolySnake | https://openaccess.thecvf.com/content/WACV2025/html/Ruan_Physiology-Aware_PolySnake_for_Coronary_Vessel_Segmentation_WACV_2025_paper.html | 0 | Physiology-Aware PolySnake for Coronary Vessel Segmentation
Coronary artery disease (CAD) is a significant health risk that requires early detection for effective treatment. While recent advances in deep learning have shown promise in automating CAD detection from coronary computed tomography angiography (CCTA) images ... | [
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wacv_2025_f6a15d5df3 | f6a15d5df3 | wacv | 2,025 | PivotAlign: Improve Semi-Supervised Learning by Learning Intra-Class Heterogeneity and Aligning with Pivots | Self-supervised learning plays an important role in current state-of-the-art semi-supervised learning (SSL) methods. These methods learn inter-class heterogeneity among data and generate pseudo-labels based on class level representations. However they often neglect intra-class heterogeneity resulting in the under-explo... | Lingjie Yi; Tao Sun; Yikai Zhang; Songzhu Zheng; Weimin Lyu; Haibin Ling; Chao Chen | Stony Brook University; Stony Brook University; Morgan Stanley; Morgan Stanley; Stony Brook University; Stony Brook University; Stony Brook University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yi_PivotAlign_Improve_Semi-Supervised_Learning_by_Learning_Intra-Class_Heterogeneity_and_Aligning_WACV_2025_paper.html | 0 | PivotAlign: Improve Semi-Supervised Learning by Learning Intra-Class Heterogeneity and Aligning with Pivots
Self-supervised learning plays an important role in current state-of-the-art semi-supervised learning (SSL) methods. These methods learn inter-class heterogeneity among data and generate pseudo-labels based on cl... | [
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wacv_2025_c1df1e88f9 | c1df1e88f9 | wacv | 2,025 | Pix2Poly: A Sequence Prediction Method for End-to-End Polygonal Building Footprint Extraction from Remote Sensing Imagery | Extraction of building footprint polygons from remotely sensed data is essential for several urban understanding tasks such as reconstruction navigation & mapping. Despite significant progress in the area extracting accurate polygonal vector building footprints remains an open problem. In this paper we introduce Pix2Po... | Yeshwanth Kumar Adimoolam; Charalambos Poullis; Melinos Averkiou | CYENS CoE, Cyprus; Concordia University; CYENS CoE, Cyprus | Poster | main | https://github.com/yeshwanth95/Pix2Poly | https://openaccess.thecvf.com/content/WACV2025/html/Adimoolam_Pix2Poly_A_Sequence_Prediction_Method_for_End-to-End_Polygonal_Building_Footprint_WACV_2025_paper.html | 1 | 2412.07899 | Pix2Poly: A Sequence Prediction Method for End-to-End Polygonal Building Footprint Extraction from Remote Sensing Imagery
Extraction of building footprint polygons from remotely sensed data is essential for several urban understanding tasks such as reconstruction navigation & mapping. Despite significant progress in th... | [
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wacv_2025_7c8092cf8a | 7c8092cf8a | wacv | 2,025 | PixSwap: High-Resolution Face Swapping for Effective Reflection of Identity via Pixel-Level Supervision with Synthetic Paired Dataset | Face swapping is to interchange identity features such as eyes nose and lips between a source and a target face while preserving the target attributes like expression pose skin color and hair. Despite considerable advancements in quality over the years recent studies conducting high-resolution face swapping still encou... | Taewoo Kim; Geonsu Lee; Hyukgi Lee; Seongtae Kim; Younggun Lee | Neosapience; Neosapience; Neosapience; Neosapience; Neosapience | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kim_PixSwap_High-Resolution_Face_Swapping_for_Effective_Reflection_of_Identity_via_WACV_2025_paper.html | 0 | PixSwap: High-Resolution Face Swapping for Effective Reflection of Identity via Pixel-Level Supervision with Synthetic Paired Dataset
Face swapping is to interchange identity features such as eyes nose and lips between a source and a target face while preserving the target attributes like expression pose skin color and... | [
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wacv_2025_63ad554933 | 63ad554933 | wacv | 2,025 | Pixel-Wise Shuffling with Collaborative Sparsity for Melanoma Hyperspectral Image Classification | Hyperspectral imaging has emerged as a promising technology for medical image classification particularly in skin cancer diagnosis. However current methods face significant challenges in accurately and robustly classifying non-cancerous skin lesions especially when melanoma lesions overlap with pigmented regions. Exist... | Favour Ekong; Jun Zhou; Kwabena Sarpong; Yongsheng Gao | Griffith University, Queensland, Australia; Griffith University, Queensland, Australia; Griffith University, Queensland, Australia; Griffith University, Queensland, Australia | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ekong_Pixel-Wise_Shuffling_with_Collaborative_Sparsity_for_Melanoma_Hyperspectral_Image_Classification_WACV_2025_paper.html | 0 | Pixel-Wise Shuffling with Collaborative Sparsity for Melanoma Hyperspectral Image Classification
Hyperspectral imaging has emerged as a promising technology for medical image classification particularly in skin cancer diagnosis. However current methods face significant challenges in accurately and robustly classifying ... | [
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