---
dataset_info:
  features:
  - name: scene
    dtype: int32
  - name: altitude
    dtype: int32
  - name: frame_id
    dtype: int32
  - name: image
    dtype: image
  - name: depth_map
    dtype: array3d
  - name: voxel_grid
    dtype:
      label:
        dtype: uint8
        shape:
        - 192
        - 128
        - 128
      invalid:
        dtype: bool
        shape:
        - 192
        - 128
        - 128
      occluded:
        dtype: bool
        shape:
        - 192
        - 128
        - 128
      surface:
        dtype: bool
        shape:
        - 192
        - 128
        - 128
  - name: calibration
    dtype:
      K:
        dtype: float32
        shape:
        - 3
        - 3
language:
- en
license: cc-by-nc-sa-4.0
tags:
- 3d scene understanding
- 3d-scene-completion
- aerial perception
- autonomous flying
- dataset
- benchmark
task_categories:
- image-to-3d
task_ids:
- semantic-segmentation
---

# OccuFly Dataset

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.

📚 **Full Documentation on GitHub**: [github.com/markus-42/occufly](https://github.com/markus-42/occufly)  
🌐 **Project Page**: [markus-42.github.io/publications/2026/occufly/](https://markus-42.github.io/publications/2026/occufly/)  
🤗 **Aerial DepthAnything2**: [huggingface.co/markus-42/OccuFly-DepthAnythingV2](https://huggingface.co/markus-42/OccuFly-DepthAnythingV2)  
📜 **Paper**: [arXiv:2512.20770  ](https://arxiv.org/abs/2512.20770)  


## Download and Documentation

For details on download and documentation, visit [github.com/markus-42/occufly](https://github.com/markus-42/occufly)

## Citation

If this repository or our work was helpful to you, we would appreciate citing our paper and giving the repository a like ❤️

```bibtex
@inproceedings{gross2026occufly,
    title={{OccuFly: A 3D Vision Benchmark for Semantic Scene Completion from the Aerial Perspective}}, 
    author={Markus Gross and Sai B. Matha and Aya Fahmy and Rui Song and Daniel Cremers and Henri Meess},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    year={2026},
}
```

## License

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.