Chengfeng Zhao1, Junbo Qi2, Zhiyang Dou3, Minchen Li4, Ziwei Liu5, Wenping Wang6, Yuan Liu1,5,†
1The Hong Kong University of Science and Technology
2Waseda University
3The University of Hong Kong
4Carnegie Mellon University
5Nanyang Technological University
6Texas A&M University
†Corresponding author
We tested our environment on Ubuntu 20.04 LTS
with CUDA 12.1
, gcc 9.4.0
, and g++ 9.4.0
.
conda create python=3.10 --name unic
conda activate unic
pip install torch==2.5.0 torchvision==0.20.0 torchaudio==2.5.0 --index-url https://download.pytorch.org/whl/cu121
pip install -r requirements.txt
conda install -c fvcore -c iopath -c conda-forge fvcore iopath
pip install "git+https://github.com/facebookresearch/pytorch3d.git@stable"
git clone https://github.com/unlimblue/KNN_CUDA.git
cd KNN_CUDA
make && make install
cd ..
Thanks to the following work that we refer to and benefit from:
- Codebook Matching: the categorical encoder architecture and the Unity project framework;
- NeRF-Pytorch: the neural field implementation;
- SMPL-to-FBX: the FBX Python SDK usage;
- HOOD: the visualization code
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.