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Decorrelated Adversarial Learning for Age-Invariant Face Recognition

CVPR 2019 · Label-efficient and robust learning › Recognition and long-tail · approach: Fair and quality-aware face recognition · 109 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add age classification supervision without DAL (ablation)Baseline face recognition model · FG-NET MF1rank-1 identification rate: 55.86% -> 55.84%No clear effect
add age classification supervision without DAL (ablation)Baseline face recognition model · FG-NET MF2rank-1 identification rate: 58.85% -> 58.64%No clear effect
add age classification supervision without DAL (ablation)Baseline face recognition model · MORPH Album 2rank-1 identification rate: 98.21% -> 98.11%No clear effect
add age classification supervision without DAL (ablation)Baseline face recognition model · CACD-VSverification accuracy: 99.07% -> 99.05%No clear effect
add DAL decorrelation regularization to age- and identity-supervised training (ablation)Age-supervised face recognition model · FG-NET MF1rank-1 identification rate: 55.84% -> 57.92%Helped
add DAL decorrelation regularization to age- and identity-supervised training (ablation)Age-supervised face recognition model · FG-NET MF2rank-1 identification rate: 58.64% -> 60.01%Helped
add DAL decorrelation regularization to age- and identity-supervised training (ablation)Age-supervised face recognition model · FG-NET leave-one-outrank-1 identification rate: 93.6% -> 94.5%Helped
add DAL decorrelation regularization to age- and identity-supervised training (ablation)Age-supervised face recognition model · MORPH Album 2rank-1 identification rate: 98.11% -> 98.93%Helped
add DAL decorrelation regularization to age- and identity-supervised training (ablation)Age-supervised face recognition model · CACD-VSverification accuracy: 99.05% -> 99.40%Helped
add DAL decorrelation regularization (ablation)Identity-dependent features · Small training dataset, across age groupscosine similarity to identity class centerHelped

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