Skip to content

Latest commit

 

History

History
51 lines (36 loc) · 1.38 KB

README.md

File metadata and controls

51 lines (36 loc) · 1.38 KB

AniFormer

This is the PyTorch implementation of our BMVC 2021 paper AniFormer: Data-driven 3D Animation with Transformer. Haoyu Chen, Hao Tang, Nicu Sebe, Guoying Zhao.

Citation

If you use our code or paper, please consider citing:

@inproceedings{chen2021AniFormer,
  title={AniFormer: Data-driven 3D Animation withTransformer},
  author={Chen, Haoyu and Tang, Hao and Sebe, Nicu and Zhao, Guoying},
  booktitle={BMVC},
  year={2021}
}

Dependencies

Requirements:

  • python3.6
  • numpy
  • pytorch==1.1.0 and above
  • trimesh

Dataset preparation

Please download DFAUST dataset from DFAUST link for training the model.

Generate the driving sequence based on our script:

TBD

Training

The usage of our code is easy, just run the code below.

python train.py

Acknowledgement

Part of our code is based on

3D transfer: NPT

Transformer framework: (https://github.com/lucidrains/vit-pytorch)

Many thanks!

License

MIT-2.0 License