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

SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data
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biometrics face face-recognition privacy synthetic-data

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This is the official repository of the papers:

SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data (IJCB 2022)

SFace2: Synthetic-Based Face Recognition With w-Space Identity-Driven Sampling (TBIOM 2024)

SFace

SFace2

Framework

The SFace and SFace2 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).

Model Pretrained model
SFace-KT pretrained-mode
SFace-CLS pretrained-mode
SFace-CL pretrained-mode
CASIA-WebFace pretrained-mode

If you use any of the code/data 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},
}

@ARTICLE{10454585,
  author={Boutros, Fadi and Huber, Marco and Luu, Anh Thi and Siebke, Patrick and Damer, Naser},
  journal={IEEE Transactions on Biometrics, Behavior, and Identity Science}, 
  title={SFace2: Synthetic-Based Face Recognition With w-Space Identity-Driven Sampling}, 
  year={2024},
  volume={},
  number={},
  pages={1-1},
  keywords={Face recognition;Synthetic data;Training;Data models;Data privacy;Law;Generative adversarial networks;Face Recognition;Biometrics;Generative Adversarial Networks;Synthetic-based Face Recognition},
  doi={10.1109/TBIOM.2024.3371502}}

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