SOURCE-LINKED INTELLIGENCE

DenseFace: Bias Mitigation in Face Recognition via Density-Aware Probabilistic Matching

arXiv · AI, language, vision and robotics · article · Sep 14, 2026 · UTC

Despite steady progress in face recognition, current face recognition models still suffer from significant demographic biases. While approaches for bias mitigation have been proposed, existing methods often impose constraints on the training procedure and result in the degradation of recognition accuracy. To address this issue, we here introduce a method that reduces racial bias in pre-trained face recognition models without compromising their accuracy. To this end, we model face embeddings of each person by von Mises-Fisher (MF) distribution. We next observe the dependency between demographic

Read original source ↗ Open in workspace

recordType

paper

region

Global