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 High resolution version 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!!!

High Resolution Dataset VGGFace2-HQ

Dependencies

python3.6+
pytorch1.5+
torchvision
opencv
pillow
numpy
imageio
moviepy
insightface

Usage

Preparation

Inference for image or video face swapping

Colab demo

Stronger feature

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:

[Mama(video) 1080p]

[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

[Online Video]

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}
}