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