| ---
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| license: creativeml-openrail-m
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| task_categories:
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| - image-to-image
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| - image-segmentation
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| - mask-generation
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| language:
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| - en
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| tags:
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| - satellite
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| - remote-sensing
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| - vhr
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| - diffusion
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| - inpainting
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| - geospatial
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| dataset_name: KAO-DIFFSAT-VHR-BENCHMARK
|
| ---
|
|
|
| # 🛰️ KAO-DIFFSAT-VHR-BENCHMARK
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| **High-Resolution Satellite Image Dataset for Diffusion-Based Inpainting Research**
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|
|
| 🚀 Project Page: https://kaopanboonyuen.github.io/KAO/
|
|
|
| ---
|
|
|
| ## 🌍 Overview
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|
|
| The **KAO-DIFFSAT-VHR-BENCHMARK** dataset is a curated collection of **very high-resolution (VHR) satellite imagery samples** designed for evaluating diffusion-based image inpainting methods in remote sensing.
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|
|
| This dataset is used in conjunction with our research:
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|
|
| > **KAO: Kernel-Adaptive Optimization in Diffusion for Satellite Image Inpainting**
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|
|
| 📄 Paper: https://arxiv.org/abs/2511.02462
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| 🎉 Accepted to IEEE Transactions on Geoscience and Remote Sensing (TGRS)
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| 🌏 Presented at AOGS 2026, Japan
|
|
|
| ---
|
|
|
| ## 🛰️ Dataset Description
|
|
|
| This dataset contains high-resolution satellite image samples used for:
|
|
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| - 🧠 Image inpainting benchmarking
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| - 🌍 Geospatial reconstruction tasks
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| - 🏙️ Urban / rural structure restoration
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| - 🌱 Land-cover consistency evaluation
|
|
|
| ---
|
|
|
| ## 📁 Dataset Structure
|
|
|
| ```
|
|
|
| SAMPLE_SATELLITE_IMAGE/
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| SAMPLE_SATELLITE_IMAGE_0001.jpg
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| SAMPLE_SATELLITE_IMAGE_0002.jpg
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| SAMPLE_SATELLITE_IMAGE_0003.jpg
|
| ...
|
|
|
| ````
|
|
|
| ---
|
|
|
| ## 📊 Notes
|
|
|
| - This dataset is intended for **research and benchmarking purposes**
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| - Images are used as **input samples for diffusion-based inpainting evaluation**
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| - Masks and ground-truth annotations may be released in future updates
|
|
|
| ---
|
|
|
| ## 📚 Citation
|
|
|
| If you use this dataset, please cite:
|
|
|
| ```bibtex
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| @article{panboonyuen2025kao,
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| title={KAO: Kernel-Adaptive Optimization in Diffusion for Satellite Image},
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| author={Panboonyuen, Teerapong},
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| journal={IEEE Transactions on Geoscience and Remote Sensing},
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| year={2025},
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| publisher={IEEE}
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| }
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| ````
|
|
|
| ---
|
|
|
| ## 🙏 Acknowledgements
|
|
|
| Parts of this dataset are inspired by:
|
|
|
| ```bibtex
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| @article{boguszewski2020landcoverai,
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| title={LandCover.ai: Dataset for Automatic Mapping of Buildings, Woodlands, Water and Roads from Aerial Imagery},
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| author={Boguszewski, Adrian and others},
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| journal={arXiv preprint arXiv:2005.02264},
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| year={2020}
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| }
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| ```
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|
|
| We thank the authors of **LandCover.ai** for their valuable contribution to the remote sensing community.
|
|
|
| ---
|
|
|
| ## ⚠️ Disclaimer
|
|
|
| This dataset is provided for academic and research use only.
|
|
|
| ---
|
|
|
