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Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues

CVPR 2023 · Image generation › Editing and style transfer · approach: Identity-preserving face manipulation · 5 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use ID2Albedo instead of TRUST (BalancedAlb)Facial albedo estimation · FAIR benchmarkAvg. ITA: 13.87 -> 12.07Helped
Use ID2Albedo instead of TRUST (BalancedAlb)Facial albedo estimation · FAIR benchmarkBias: 2.79 -> 4.91Hurt
Use ID2Albedo instead of TRUSTFacial albedo estimation · FFHQM-SSIM: 0.64 -> 0.87Helped
Use a subspace-based GAN rather than StyleGANv2-ADA (ablation)Albedo generator · Aligned UV albedo dataFID: 49.3 -> 42.2Helped
Freeze the ArcFace encoder rather than fine-tuning it (ablation)ID2Albedo · FAIR benchmarkAvg. ITA: 14.58 -> 13.46Helped
Use illumination-robust ArcFace identity features instead of a scratch-trained ResNet-100 (ablation)Albedo encoder · FAIR benchmarkAvg. ITA: 58.46 -> 13.46Helped
Add CLIP-based multiple-attribute cues (ablation)ID2Albedo · FAIR benchmarkAvg. ITA: 25.66 -> 13.46Helped
Add CLIP cues for attributes beyond race (ablation)ID2Albedo · FAIR benchmarkAvg. ITA: 16.21 -> 13.46Helped
Replace CLIP cues with manually labeled race cues (ablation)ID2Albedo · FAIR benchmarkAvg. ITA: 13.46 -> 18.13Hurt

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