Paper

Racial Faces in-the-Wild: Reducing Racial Bias by Information Maximization Adaptation Network

Racial bias is an important issue in biometric, but has not been thoroughly studied in deep face recognition. In this paper, we first contribute a dedicated dataset called Racial Faces in-the-Wild (RFW) database, on which we firmly validated the racial bias of four commercial APIs and four state-of-the-art (SOTA) algorithms... (read more)

Results in Papers With Code
(↓ scroll down to see all results)