# 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 [![simswaplogo](/doc/img/logo1.png)](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 ![Results1](/doc/img/results1.PNG) ![Results2](/doc/img/total.PNG) **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** [![logo](./doc/img/logo.png)](https://github.com/neuralchen/ASMAGAN) [![title](/doc/img/title.png)](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)