AI RESEARCH
LH2Face: Loss function for Hard High-quality Face
arXiv CS.CV
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ArXi:2506.23555v4 Announce Type: replace In current practical face authentication systems, most face recognition (FR) algorithms are based on cosine similarity with softmax classification. Despite its reliable classification performance, this method struggles with hard samples. A popular strategy to improve FR performance is incorporating angular or cosine margins. However, it does not take face quality or recognition hardness into account, simply increasing the margin value and thus causing an overly uniform