# Neural-Pose-Transfer

**Repository Path**: lilujunai/Neural-Pose-Transfer

## Basic Information

- **Project Name**: Neural-Pose-Transfer
- **Description**: Neural Pose Transfer by Spatially Adaptive Instance Normalization. In CVPR 2020
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-22
- **Last Updated**: 2021-03-24

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Neural-Pose-Transfer

This is an implementation of the CVPR'20 paper "Neural Pose Transfer by Spatially Adaptive Instance Normalization".

Please check our [paper](https://arxiv.org/abs/2003.07254) and the [project webpage](https://jiashunwang.github.io/Neural-Pose-Transfer/) for more details.

#### Citation

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}
}
```

## Dependencies

Requirements:
- python3.6
- numpy
- pytorch==1.1.0
- [pymesh](https://pymesh.readthedocs.io/en/latest/)

Our code has been tested with Python 3.6, Pytorch1.1.0, CUDA 9.0 on Ubuntu 16.04.

## Training
```
python train.py
```

## Acknowledgement
Part of our code is based on [SPADE](https://github.com/NVlabs/SPADE)，[3D-CODED](https://github.com/ThibaultGROUEIX/3D-CODED) and [pointnet.pytorch](https://github.com/fxia22/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).

## License
Apache-2.0 License