SimSwap: An Efficient Framework For High Fidelity Face Swapping
Proceedings of the 28th ACM International Conference on Multimedia
The official repository with Pytorch
Our method can realize arbitrary face swapping on images and videos with one single trained model.
Currently, only the test code is available. Training scripts are coming soon......
The high resolution version of SimSwap-HQ is supported!
Our paper can be downloaded from [Arxiv] [ACM DOI]
Attention
This project is for technical and academic use only. Please do not apply it to illegal and unethical scenarios.
Please do not ignore the content at the end of this README!
If you find this project useful, please star it. It is the greatest appreciation of our work.
Top News
2021-11-24
: We have trained a beta version of SimSwap-HQ on VGGFace2-HQ and open sourced the checkpoint of this model (if you think the Simswap 512 is cool, please star our VGGFace2-HQ repo). Please don’t forget to go to Preparation and Inference for image or video face swapping to check the latest set up.
2021-11-23
: The google drive link of VGGFace2-HQ is released.
2021-11-17
: We released a high resolution face dataset VGGFace2-HQ and the method to generate this dataset. This dataset is for research purpose.
2021-08-30
: Docker has been supported, please refer here for details.
2021-08-17
: We have updated the Preparation, The main change is that the gpu version of onnx is now installed by default, Now the time to process a video is greatly reduced.
2021-07-19
: Obvious border abruptness has been resolved. We add the ability to using mask and upgrade the old algorithm for better visual effect, please go to Inference for image or video face swapping for details. Please don’t forget to go to Preparation to check the latest set up. (Thanks for the help from @woctezuma and @instant-high)
The first open source high resolution dataset for face swapping!!!
VGGFace2-HQ
High Resolution DatasetDependencies
- python3.6+
- pytorch1.5+
- torchvision
- opencv
- pillow
- numpy
- imageio
- moviepy
- insightface
Usage
Inference for image or video face swapping
Colab fo switching specific faces in multi-face videos
Image face swapping demo & Docker image on Replicate
Training: coming soon
Video
Results
High-quality videos can be found in the link below:
[Google Drive link for video 1]
[Google Drive link for video 2]
[Google Drive link for video 3]
[Baidu Drive link for video] Password: b26n
User case
If you have some interesting results after using our project and are willing to share, you can contact us by email or share directly on the issue. Later, we may make a separate section to show these results, which should be cool.
At the same time, if you have suggestions for our project, please feel free to ask questions in the issue, or contact us directly via email: email1, email2, email3. (All three can be contacted, just choose any one)
License
For academic and non-commercial use only.The whole project is under the CC-BY-NC 4.0 license. See LICENSE for additional details.
To cite our paper
@inproceedings{DBLP:conf/mm/ChenCNG20,
author = {Renwang Chen and
Xuanhong Chen and
Bingbing Ni and
Yanhao Ge},
title = {SimSwap: An Efficient Framework For High Fidelity Face Swapping},
booktitle = {{MM} '20: The 28th {ACM} International Conference on Multimedia},
pages = {2003--2011},
publisher = {{ACM}},
year = {2020}
}
Related Projects
Please visit our another ACMMM2020 high-quality style transfer project
Please visit our AAAI2021 sketch based rendering project
Please visit our high resolution face dataset VGGFace2-HQ
Learn about our other projects