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Learning to Attract and Repel: Dual Quality Margin Learning for Face Recognition (DQM-Face)

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

Face recognition in unconstrained environments remains highly challenging due to diverse and extreme variations encountered in real-world scenarios. To mitigate these effects, existing margin-based approaches model sample quality through feature magnitude. However, magnitude-based modeling alone is susceptible to identity-agnostic noise, which can degrade the reliability and discriminative power of learned representations. In this paper, we propose Dual Quality Margin Learning for Face Recognition (DQM-Face), a novel framework that enables refined attraction and repulsion dynamics during repre

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