Bias Mitigation in Face Recognition via Demographic-based Supervised Contrastive Learning
The Demographic-based Supervised Contrastive loss (DeSCon) for face recognition is proposed, which relies on a well-designed composition of training batches and demographic-aware pair selection and can improve fairness beyond balancing training datasets while maintaining competitive verification performance.