h Index

Racial equality is an important theme of international human rights law, but it has been largely obscured when the overall face recognition accuracy is pursued blindly. More facts indicate racial bias indeed degrades the fairness of recognition system and the error rates on non-Caucasians are usually much higher than Caucasians. To facilitate the research towards this issue, we construct four training datasets and one testing dataset with different races for deep face recognition.



Four million-scale training datasets with different ethnicity distributions are provided.



RFW (Racial Faces in-the-Wild) database for fairly evaluating the performance of different races are provided.



Different models and evaluation code are provided.


Contact Us

Please contact Mei Wang and Weihong Deng for questions about the database.