Datasets:
Tasks:
Image-to-3D
Sub-tasks:
semantic-segmentation
Languages:
English
ArXiv:
Tags:
3d scene understanding
3d-scene-completion
aerial perception
autonomous flying
dataset
benchmark
License:
minor changes
Browse files
README.md
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# OccuFly Dataset
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Following its acceptance as a
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π **Project Page**: [markus-42.github.io/publications/2026/occufly/](https://markus-42.github.io/publications/2026/occufly/)
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π€ **Aerial DepthAnything2**: [huggingface.co/markus-42/OccuFly-DepthAnythingV2](https://huggingface.co/markus-42/OccuFly-DepthAnythingV2)
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π **Full Documentation GitHub**: See [github.com/markus-42/occufly](https://github.com/markus-42/occufly)
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---
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## Quick Start
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### 1. Install Dependencies
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```bash
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pip install huggingface-hub tqdm numpy Pillow
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```
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### 2. Download Dataset
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# Download all scenes
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python download_occufly.py
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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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# Download specific scenes (1-9)
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python download_occufly.py --scenes 1 2 3
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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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# Download only predicted depth maps
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python download_occufly.py --only_depth_predictions
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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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## Dataset Splits
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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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Each scene has 3 altitudes: 30m, 40m, 50m
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## Full Documentation
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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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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
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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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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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π **Full Documentation on GitHub**: [github.com/markus-42/occufly](https://github.com/markus-42/occufly)
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π **Project Page**: [markus-42.github.io/publications/2026/occufly/](https://markus-42.github.io/publications/2026/occufly/)
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π€ **Aerial DepthAnything2**: [huggingface.co/markus-42/OccuFly-DepthAnythingV2](https://huggingface.co/markus-42/OccuFly-DepthAnythingV2)
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π **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 β€οΈ
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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.
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