/TransFace-ByteFace

Rethinking the Face Recognition Paradigm with a Focus on Efficiency, Security, and Precision.

Primary LanguagePython

TransFace-ByteFace

  • Code for the following papers:

(1) Transface: Calibrating transformer training for face recognition from a data-centric perspective, IEEE/CVF International Conference on Computer Vision (ICCV), 2023. (Conference version)

(2) Rethinking the Face Recognition Paradigm with a Focus on Efficiency, Security, and Precision. (Under Review).

Codes for TransFace and ByteFace models are respectively in folders TransFace and ByteFace.

Citation

  • If you find it helpful for you, please cite our paper
@inproceedings{dan2023transface,
  title={TransFace: Calibrating Transformer Training for Face Recognition from a Data-Centric Perspective},
  author={Dan, Jun and Liu, Yang and Xie, Haoyu and Deng, Jiankang and Xie, Haoran and Xie, Xuansong and Sun, Baigui},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={20642--20653},
  year={2023}
}

Acknowledgments

We thank Insighface for the excellent code base.