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.
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}
}
Requirements:
- python3.6
- numpy
- pytorch==1.1.0 and above
- trimesh
Please download DFAUST dataset from DFAUST link for training the model.
Generate the driving sequence based on our script:
TBD
The usage of our code is easy, just run the code below.
python train.py
Part of our code is based on
3D transfer: NPT，
Transformer framework: (https://github.com/lucidrains/vit-pytorch)
Many thanks!
MIT-2.0 License