This is an implementation of the CVPR'20 paper "Neural Pose Transfer by Spatially Adaptive Instance Normalization".
Please check our paper and the project webpage for more details.
If you use this code for any purpose, please consider citing:
@inProceedings{wang2020npt,
title={Neural Pose Transfer by Spatially Adaptive Instance Normalization},
author={Jiashun Wang and Chao Wen and Yanwei Fu and Haitao Lin and Tianyun Zou and Xiangyang Xue and Yinda Zhang},
booktitle={CVPR},
year={2020}
}
Requirements:
- python3.6
- numpy
- pytorch==1.1.0
- pymesh
Our code has been tested with Python 3.6, Pytorch1.1.0, CUDA 9.0 on Ubuntu 16.04.
python train.py
Part of our code is based on SPADE,3D-CODED and pointnet.pytorch. Many thanks!
This work was supported in part by NSFC Projects (U1611461), Science and Technology Commission of Shanghai Municipality Projects (19511120700, 19ZR1471800), Shanghai Municipal Science and Technology Major Project (2018SHZDZX01), and Shanghai Research and Innovation Functional Program (17DZ2260900).
Apache-2.0 License