Face verification data with priority to balance in gender, ethnicity, and identity.

Facial Recognition: AI that People Can Trust!

The Problems of Bias in AI: Labeled Faces and Benchmark Dataset

Our paper — FR: Too bias, or Not Too Bias? — published as part of The Workshop of Fair, Data-Efficient, and Trusted Computer Vision held in conjunction with the 2020 Conference on Computer Vision and Pattern Recognition (CVPR).