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Source code for paper WALT3D: Generating Realistic Training Data from Time-Lapse Imagery for Reconstructing Dynamic Objects under Occlusion (CVPR 2024 Oral)

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# WALT3D: Generating Realistic Training Data from Time-Lapse Imagery for Reconstructing Dynamic Objects under Occlusion

**CVPR 2024 (Oral, Top 90/11532)**

[![Project page](https://img.shields.io/badge/Project-Website-1081c2)](https://www.cs.cmu.edu/~walt3d/)
[![arXiv](https://img.shields.io/badge/arXiv-2312.02158-darkred)](https://arxiv.org/abs/2403.19022)

**WALT3D: Generating Realistic Training Data from Time-Lapse Imagery for Reconstructing Dynamic Objects under Occlusion**

[Khiem Vuong](https://www.khiemvuong.com/)1,
[N. Dinesh Reddy](https://dineshreddy91.github.io/)2,
[Robert Tamburo](https://www.ri.cmu.edu/ri-people/robert-joseph-tamburo/)1,
[Srinivasa G. Narasimhan](https://www.cs.cmu.edu/~srinivas/)1

1Carnegie Mellon University
2Amazon

![teaser](https://raw.githubusercontent.com/kvuong2711/WALT3D/main/media/teaser_image.jpg)

## Code release status (ETA: July)
- [ ] Demo code and checkpoints
- [ ] Data generation code 
- [ ] Vehicle keypoints dataset release

## Citing WALT3D

If you find this code helpful, please cite:

```
@InProceedings{vuong2024walt3d,
    title={WALT3D: Generating Realistic Training Data from Time-Lapse Imagery for Reconstructing Dynamic Objects under Occlusion},
    author={Vuong, Khiem and Reddy, N Dinesh and Tamburo, Robert and Narasimhan, Srinivasa G},
    booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    year={2024}
}
```

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