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Research questionHow can face recognition separate identity-relevant features from noise in unconstrained images?Unconstrained face images vary widely, and feature magnitude can reflect nuisance noise rather than identity-relevant information. This makes it difficult to improve within-identity consistency without weakening separation between identities.
AI
Computer Vision
Image & Video Processing
Machine Learning
Latest papersRecent research connected to this question, newest first.Learning to Attract and Repel: Dual Quality Margin Learning for Face Recognition (DQM-Face)The paper presents DQM-Face, which combines magnitude-based and semantic quality cues with attraction and repulsion margins for face recognition. It reports results on multiple challenging face-recognition benchmarks and examines the learned quality signal for face-image quality assessment.research paper · Sep 2, 2026
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