The paper: https://openaccess.thecvf.com/content/WACV2021/papers/Karkkainen_FairFace_Face_Attribute_Dataset_for_Balanced_Race_Gender_and_Age_WACV_2021_paper.pdf

Karkkainen, K., & Joo, J. (2021). FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 1548-1558).

If you use our dataset or model in your paper, please cite:

    @inproceedings{karkkainenfairface,
      title={FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation},
      author={Karkkainen, Kimmo and Joo, Jungseock},
      booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
      year={2021},
      pages={1548--1558}
    }

https://github.com/dchen236/FairFace

Images (train + validation set): [Padding=0.25], [Padding=1.25]

• We used dlib's get_face_chip() to crop and align faces with padding = 0.25 in the main experiments (less margin) and padding = 1.25 for the bias measument experiment for commercial APIs.

Labels: Train Validation

License: CC BY 4.0