- Create a conda environment
conda env create -f environment.yaml - Install Pytorch3d
pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py38_cu113_pyt1120/download.html - Download our dataset Google drive and place it in this folder
python train.py
During the training process, the intermediate results are saved in the results folder
@inproceedings{xu2023avatarmav,
title={AvatarMAV: Fast 3D Head Avatar Reconstruction Using Motion-Aware Neural Voxels},
author={Xu, Yuelang and Wang, Lizhen and Zhao, Xiaochen and Zhang, Hongwen and Liu, Yebin},
booktitle={ACM SIGGRAPH 2023 Conference Proceedings},
year={2023}
}