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YuliangXiu / PuzzleAvatar

[SIGGRAPH Asia 2024] PuzzleAvatar: Assembling 3D Avatars from Personal Albums
https://puzzleavatar.is.tue.mpg.de/
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PuzzleAvatar:
Assembly of Avatar from Unconstrained Photo Collections

Yuliang Xiu · Yufei Ye · Zhen Liu · Dimitris Tzionas · Michael J. Black

SIGGRAPH Asia 2024 (Journal Track)


Paper PDF Project Page youtube views

PuzzleAvatar reconstructs a textured 3D clothed human from **unconstrained photo collections**. | Works On | Without Requiring or Being Limited by | | :-------------------------------: | :---------------------------------------------: | | ✅ Any number of photos | ❌ Human body pose (3D HPS, 2D Keypoints, etc.) | | ✅ In any poses | ❌ Camera pose | | ✅ From any views | ❌ Geometric cues (depth, normal, etc.) | | ✅ With any cropping or occlusion | ❌ Re-projection losses | | ✅ Any A-posed body mesh template | ❌ SMPL-(X/H), GHUM, Frank, Adam, SCAPE, etc |


News :triangular_flag_on_post:


Getting Started

  1. Set up the paths in scripts/env.sh.
  2. Please follow the Installation Instruction to setup all the required packages.
  3. Run PuzzleAvatar (Grounded-SAM $\rightarrow$ PuzzleBooth $\rightarrow$ SDS, takes about 4 hours)
# For custom data
bash scripts/run.sh data/human/yuliang results/human/yuliang human_yuliang

# For PuzzleIOI
bash scripts/run.sh data/PuzzleIOI/puzzle_capture/03632/outfit13 results/PuzzleIOI/puzzle_capture/03632/outfit13 03632_outfit13

The results will be saved in the experiment folder results/human/yuliang, and results/PuzzleIOI/puzzle_capture/03632/outfit13.

Dataset and Benchmark

  1. Register at puzzleavatar.is.tue.mpg.de
  2. Download datasets (194GB) with registered username and password 
    bash scripts/fetch_data.sh
  3. For evaluation / benchmark 
    
# render the reconstruction results (4 views)
# If the rendering process is stuck, please refer to the changes for PRT computation:
# https://github.com/YuliangXiu/ICON/pull/237/files

python -m render.render_batch_result -headless -out_dir ./results/ -split test

calculate both 3D metrics (Chamfer, P2S, NC) and 2D metrics (PSNR, SSIM, LPIPS)

python -m multi_concepts.benchmark -split test


## Acknowledgment

This implementation is built based on [TeCH](https://github.com/huangyangyi/TeCH), [Break-A-Scene](https://github.com/google/break-a-scene), [Grounded SAM](https://github.com/IDEA-Research/Grounded-Segment-Anything), [GPT-4V(ision)](https://openai.com/index/gpt-4v-system-card/), [Stable Diffusion 2-1-base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base), [BOFT-DreamBooth](https://github.com/huggingface/peft/blob/main/examples/boft_dreambooth/train_dreambooth.py), [Stable Dreamfusion](https://github.com/ashawkey/stable-dreamfusion), [ECON](https://github.com/YuliangXiu/ECON).

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No.860768 ([CLIPE Project](https://www.clipe-itn.eu))

Kudos to all of our amazing contributors! PuzzleAvatar thrives through open-source. In that spirit, we welcome all kinds of contributions from the community.

<a href="https://github.com/yuliangxiu/PuzzleAvatar/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=yuliangxiu/PuzzleAvatar" />
</a>

_Contributor avatars are randomly shuffled._

## License

This code and model are available for non-commercial scientific research purposes as defined in the [LICENSE](LICENSE) file. By downloading and using the code and model you agree to the terms in the [LICENSE](LICENSE).

## Disclosure

MJB has received research gift funds from Adobe, Intel, Nvidia, Meta/Facebook, and Amazon. MJB has financial interests in Amazon and Meshcapade GmbH. While MJB is a co-founder and Chief Scientist at Meshcapade, his research in this project was performed solely at, and funded solely by, the Max Planck Society.

## Contact

For technical questions, please contact yuliang.xiu@tue.mpg.de

For commercial licensing, please contact ps-licensing@tue.mpg.de

## Citation

```bibtex
@article{xiu2024puzzleavatar,
  title={PuzzleAvatar: Assembling 3D Avatars from Personal Albums},
  author={Xiu, Yuliang and Ye, Yufei and Liu, Zhen and Tzionas, Dimitrios and Black, Michael J},
  journal={ACM Transactions on Graphics (TOG)},
  year={2024},
  publisher={ACM New York, NY, USA}
}

PuzzleAvatar is mainly built upon TeCH, please also kindly cite it

@inproceedings{huang2024tech,
  title={{TeCH: Text-guided Reconstruction of Lifelike Clothed Humans}},
  author={Huang, Yangyi and Yi, Hongwei and Xiu, Yuliang and Liao, Tingting and Tang, Jiaxiang and Cai, Deng and Thies, Justus},
  booktitle={International Conference on 3D Vision (3DV)},
  year={2024}
}