fit SMPL model using 3D joints
We have tested the code on Ubuntu 18.04/20.04 with CUDA 10.2/11.3
First you have to make sure that you have all dependencies in place. The simplest way to do is to use the anaconda.
You can create an anaconda environment called fit3d
using
conda env create -f environment.yaml
conda activate fit3d
Download SMPL Female and Male and SMPL Netural, and rename the files and extract them to <current directory>/smpl_models/smpl/
, eventually, the <current directory>/smpl_models
folder should have the following structure:
smpl_models
└-- smpl
└-- SMPL_FEMALE.pkl
└-- SMPL_MALE.pkl
└-- SMPL_NEUTRAL.pkl
python fit_seq.py --files test_motion2.npy
The results will locate in ./demo/demo_results/
If you find this project useful for your research, please consider citing:
@article{zuo2021sparsefusion,
title={Sparsefusion: Dynamic human avatar modeling from sparse rgbd images},
author={Zuo, Xinxin and Wang, Sen and Zheng, Jiangbin and Yu, Weiwei and Gong, Minglun and Yang, Ruigang and Cheng, Li},
journal={IEEE Transactions on Multimedia},
volume={23},
pages={1617--1629},
year={2021}
}
We indicate if a function or script is borrowed externally inside each file. Here are some great resources we benefit:
- Shape/Pose prior and some functions are borrowed from VIBE.
- SMPL models and layer is from SMPL-X model.
- Some functions are borrowed from HMR-pytorch.