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CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition

CVPR 2020 · Label-efficient and robust learning › Recognition and long-tail · approach: Margin-based face recognition losses · 590 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use CurricularFace instead of ArcFaceResNet100 face recognition · CFP-FPverification accuracy (%): 98.27 -> 98.37Helped
Use CurricularFace instead of ArcFaceResNet100 face recognition · IJB-B 1:1 verification TAR (@FAR=1e-4)TAR (%): 94.2 -> 94.8Helped
Use CurricularFace instead of ArcFaceResNet100 face recognition · IJB-C 1:1 verification TAR (@FAR=1e-4)TAR (%): 95.6 -> 96.1Helped
Adapt t during training rather than fixing it (ablation)CurricularFace · LFWverification accuracy (%): 99.45 -> 99.47Helped
Adapt t during training rather than fixing it (ablation)CurricularFace · CFP-FPverification accuracy (%): 93.94 -> 96.96Helped
Estimate t with mean positive cosine similarity instead of its mode (ablation)CurricularFace · CFP-FPverification accuracy (%): 96.49 -> 96.96Helped
Estimate t with mean positive cosine similarity instead of mean predicted probability (ablation)CurricularFace · CFP-FPverification accuracy (%): 95.39 -> 96.96Helped
Train with CurricularFace instead of ArcFace at margin m=0.5 (ablation)MobileFaceNet trained on CASIA-WebFace · LFWverification accuracy (%): ArcFace does not converge; CurricularFace 99.25%Helped
Train with CurricularFace instead of ArcFace at margin m=0.45 (ablation)MobileFaceNet trained on CASIA-WebFace · LFWverification accuracy (%): 99.10% -> 99.20%Helped

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