# 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
[](https://github.com/neuralchen/SimSwap)
Our paper can be downloaded from [[Arxiv]](https://arxiv.org/pdf/2106.06340v1.pdf) [[ACM DOI]](https://dl.acm.org/doi/10.1145/3394171.3413630)
## 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
[Preparation](./doc/guidance/preparation.md)
[Inference for image or video face swapping](./doc/guidance/usage.md)
[Colab demo](https://colab.research.google.com/github/neuralchen/SimSwap/blob/main/SimSwap%20colab.ipynb)
Training: **coming soon**
## Video
## Results


**High-quality videos can be found in the link below:**
[[Mama(video) 1080p]](https://drive.google.com/file/d/1JTruy6BTnT1EK1PSaZ4x-F8RhtZU_kT3/view?usp=sharing)
[[Google Drive link for video 1]](https://drive.google.com/file/d/1hdne7Gw39d34zt3w1NYV3Ln5cT8PfCNm/view?usp=sharing)
[[Google Drive link for video 2]](https://drive.google.com/file/d/1bDEg_pVeFYLnf9QLSMuG8bsjbRPk0X5_/view?usp=sharing)
[[Google Drive link for video 3]](https://drive.google.com/file/d/1oftHAnLmgFis4XURcHTccGSWbWSXYKK1/view?usp=sharing)
[[Baidu Drive link for video]](https://pan.baidu.com/s/1WTS6jm2TY17bYJurw57LUg ) Password: ```b26n```
[[Online Video]](https://www.bilibili.com/video/BV12v411p7j5/)
## 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**
[](https://github.com/neuralchen/ASMAGAN)
[](https://github.com/neuralchen/ASMAGAN)
Learn about our other projects
[[RainNet]](https://neuralchen.github.io/RainNet);
[[Sketch Generation]](https://github.com/TZYSJTU/Sketch-Generation-with-Drawing-Process-Guided-by-Vector-Flow-and-Grayscale);
[[CooGAN]](https://github.com/neuralchen/CooGAN);
[[Knowledge Style Transfer]](https://github.com/AceSix/Knowledge_Transfer);
[[SimSwap]](https://github.com/neuralchen/SimSwap);
[[ASMA-GAN]](https://github.com/neuralchen/ASMAGAN);
[[SNGAN-Projection-pytorch]](https://github.com/neuralchen/SNGAN_Projection)
[[Pretrained_VGG19]](https://github.com/neuralchen/Pretrained_VGG19).
## Acknowledgements
* [Insightface](https://github.com/deepinsight/insightface)