GitHub - neuralchen/SimSwap: The official project of SimSwap (ACM MM 2020)
source link: https://github.com/neuralchen/SimSwap
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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
Our paper can be downloaded from [Arxiv] [ACM DOI]
Top News
2021-06-20
: We release the scripts for arbitrary video and image processing, and a colab demo.
Dependencies
- python3.6+
- pytorch1.5+
- torchvision
- opencv
- pillow
- numpy
- imageio
- moviepy
- insightface
Usage
Inference for image or video face swapping
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)
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},
url = {https://doi.org/10.1145/3394171.3413630},
doi = {10.1145/3394171.3413630},
timestamp = {Thu, 15 Oct 2020 16:32:08 +0200},
biburl = {https://dblp.org/rec/conf/mm/ChenCNG20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Related Projects
Please visit our another ACMMM2020 high-quality style transfer project
Learn about our other projects [RainNet];
Acknowledgements
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