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  # OccuFly Dataset
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- Following its acceptance as a **CVPR 2026 Oral**, we release OccuFly: the first real-world, large-scale camera-based benchmark for Semantic Scene Completion (SSC) and Metric Monocular Depth Estimation from the aerial perspective.
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  🌐 **Project Page**: [markus-42.github.io/publications/2026/occufly/](https://markus-42.github.io/publications/2026/occufly/)
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  πŸ€— **Aerial DepthAnything2**: [huggingface.co/markus-42/OccuFly-DepthAnythingV2](https://huggingface.co/markus-42/OccuFly-DepthAnythingV2)
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- πŸ“„ **Paper**: [arXiv:2512.20770 ](https://arxiv.org/abs/2512.20770)
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- πŸ“š **Full Documentation GitHub**: See [github.com/markus-42/occufly](https://github.com/markus-42/occufly)
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- ---
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-
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- ## Quick Start
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-
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- ### 1. Install Dependencies
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-
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- ```bash
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- pip install huggingface-hub tqdm numpy Pillow
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- ```
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-
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- ### 2. Download Dataset
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- Use the download script located in this repository:
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- ```bash
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- # Download all scenes
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- python download_occufly.py
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-
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- # Download specific split
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- python download_occufly.py --split train
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- python download_occufly.py --split validation
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- python download_occufly.py --split test
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-
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- # Download specific scenes (1-9)
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- python download_occufly.py --scenes 1 2 3
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-
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- # Include predicted depth maps
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- python download_occufly.py --include_depth_predictions
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- python download_occufly.py --split train --include_depth_predictions
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-
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- # Download only predicted depth maps
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- python download_occufly.py --only_depth_predictions
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-
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- # Custom output directory
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- python download_occufly.py --output ./my_data
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- ```
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-
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- ## Dataset Splits
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-
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- - **Train**: Scenes 1-5
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- - **Validation**: Scenes 6-7
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- - **Test**: Scenes 8-9
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-
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- Each scene has 3 altitudes: 30m, 40m, 50m
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-
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- ## Full Documentation
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-
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- For detailed documentation, visit [github.com/markus-42/occufly](https://github.com/markus-42/occufly).
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  ## Citation
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- ```bibtex
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- @inproceedings{gross2025occufly,
 
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  title={{OccuFly: A 3D Vision Benchmark for Semantic Scene Completion from the Aerial Perspective}},
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  author={Markus Gross and Sai B. Matha and Aya Fahmy and Rui Song and Daniel Cremers and Henri Meess},
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  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
@@ -132,10 +89,4 @@ For detailed documentation, visit [github.com/markus-42/occufly](https://github.
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  ## License
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- This dataset is licensed under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International** (CC BY-NC-SA 4.0) license.
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-
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- - **You can**: Share and adapt the material for non-commercial purposes
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- - **You must**: Give credit, indicate changes, and use the same license for derivative works
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- - **You cannot**: Use the material for commercial purposes without permission
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-
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- For full license details, see [creativecommons.org/licenses/by-nc-sa/4.0/](https://creativecommons.org/licenses/by-nc-sa/4.0/)
 
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  # OccuFly Dataset
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+ Following its acceptance as a [CVPR 2026 Oral](https://cvpr.thecvf.com/virtual/2026/oral/40308), we release OccuFly: the first real-world, large-scale camera-based benchmark for Semantic Scene Completion and Metric Monocular Depth Estimation from the aerial perspective.
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+ πŸ“š **Full Documentation on GitHub**: [github.com/markus-42/occufly](https://github.com/markus-42/occufly)
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  🌐 **Project Page**: [markus-42.github.io/publications/2026/occufly/](https://markus-42.github.io/publications/2026/occufly/)
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  πŸ€— **Aerial DepthAnything2**: [huggingface.co/markus-42/OccuFly-DepthAnythingV2](https://huggingface.co/markus-42/OccuFly-DepthAnythingV2)
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+ πŸ“œ **Paper**: [arXiv:2512.20770 ](https://arxiv.org/abs/2512.20770)
 
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+ ## Download and Documentation
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+ For details on download and documentation, visit [github.com/markus-42/occufly](https://github.com/markus-42/occufly)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Citation
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+ If this repository or our work was helpful to you, we would appreciate citing our paper and giving the repository a like ❀️
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+ ```bibtex
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+ @inproceedings{gross2026occufly,
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  title={{OccuFly: A 3D Vision Benchmark for Semantic Scene Completion from the Aerial Perspective}},
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  author={Markus Gross and Sai B. Matha and Aya Fahmy and Rui Song and Daniel Cremers and Henri Meess},
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  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
 
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  ## License
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+ This work is licensed under the [CC BY-NC-SA 4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/). See the LICENSE file for the full legal terms.