SFace-Privacy-friendly-and-Accurate-Face-Recognition-using-Synthetic-Data

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This is the official repository of the paper:

SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data

Paper on arxiv: arxiv

Accepted IJCB 2022

The SFace dataset can be downloaded from Data. (please share your name, affiliation, and official email in the request form).

The pretrained model to generate SFace dataset can be downloaded SFace.

(please share your name, affiliation, and official email in the request form).

If you use any of the code provided in this repository, please cite the following paper:

Citation

@inproceedings{Sface_Boutros,
  author    = {Fadi Boutros and
               Marco Huber and
               Patrick Siebke and
               Tim Rieber and
               Naser Damer},
  title     = {SFace: Privacy-friendly and Accurate Face Recognition using Synthetic
               Data},
  booktitle = {{IEEE} International Joint Conference on Biometrics, {IJCB} 2022,
               Abu Dhabi, United Arab Emirates, October 10-13, 2022},
  pages     = {1--11},
  publisher = {{IEEE}},
  year      = {2022},
  url       = {https://doi.org/10.1109/IJCB54206.2022.10007961},
  doi       = {10.1109/IJCB54206.2022.10007961},
}

License

This project is licensed under the terms of the Attribution-NonCommercial-ShareAlike 4.0 
International (CC BY-NC-SA 4.0) license. 
Copyright (c) 2021 Fraunhofer Institute for Computer Graphics Research IGD Darmstadt