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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

[Conference paper]

Results

Results1

Video

Dependencies

Usage

Use python3.5, pytorch1.3.0

Use this command to test the face swapping between two images:

python test_one_image.py --isTrain false --name people --Arc_path models/BEST_checkpoint.tar --pic_a_path crop_224/mars.jpg --pic_b_path crop_224/ds.jpg --output_path output/

--name refers to the checkpoint name.

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}
}
S
Description
An arbitrary face-swapping framework on images and videos with one single trained model!
Readme CC-BY-4.0 212 MiB
2021-11-23 03:06:36 +01:00
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