Created by Wenliang Zhao, Yongming Rao, Weikang Shi, Zuyan Liu, Jie Zhou, Jiwen Lu†
This repository contains PyTorch implementation for paper "DiffSwap: High-Fidelity and Controllable Face Swapping via 3D-Aware Masked Diffusion"
Please first install the environment following stable-diffusion, and then run pip install -r requirements.txt.
Please download the checkpoints from [here], and put them under the checkpoints/ folder.
The resulting file structure should be:
├── checkpoints
│ ├── diffswap.pth
│ ├── glint360k_r100.pth
│ └── shape_predictor_68_face_landmarks.dat
We provide a sample code to perform face swapping given the portrait source and target images. Please put the source images and target images in data/portrait_jpg and run
python pipeline.py
the swapped results are saved in data/portrait/swap_res_ori.
If you find our work useful in your research, please consider citing:
@article{zhao2023diffswap,
title={DiffSwap: High-Fidelity and Controllable Face Swapping via 3D-Aware Masked Diffusion},
author={Zhao, Wenliang and Rao, Yongming and Shi, Weikang and Liu, Zuyan and Zhou, Jie and Lu, Jiwen},
journal={CVPR},
year={2023}
}