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Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation

CVPR 2023 · Label-efficient and robust learning › Recognition and long-tail · approach: Loss design and classifier theory · 20 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add SCAI to HRNet HR48HRNet HR48 · COCO test-devAP: 75.5 -> 80.6Helped
Add SCAI to the strongest listed baselineCOCO test-dev · COCO test-devAP: +1.4Helped
Add SCAI to the strongest listed baselineCrowdPose test-dev · CrowdPose test-devAP: +0.9Helped
Add a correction network (ablation)Baseline HRNet HR48 · COCO test-devAP: 75.5 -> 78.5Helped
Add self-referential error feedback (ablation)Baseline + SCI with correction network · COCO test-devAP: 78.5 -> 78.9Helped
Add joint training of the correction network and FFN (ablation)Baseline + SCI with self-referential error · COCO test-devAP: 78.9 -> 79.8Helped
Add self-adaptable inference at test time (ablation)Baseline + SCI · COCO test-devAP: 79.8 -> 80.6Helped
Set λ to 0.30 instead of 0.45 (ablation)SCAI (a=0.85, b=0.65) · COCO test-devAP: 80.6 -> 80.2Hurt
Set λ to 0.60 instead of 0.45 (ablation)SCAI (a=0.85, b=0.65) · COCO test-devAP: 80.6 -> 80.4Hurt
Set a to 1.00 instead of 0.85 (ablation)SCAI (b=0.65, λ=0.45) · COCO test-devAP: 80.6 -> 80.5Hurt
Set b to 0.40 instead of 0.65 (ablation)SCAI (a=0.85, λ=0.45) · COCO test-devAP: 80.6 -> 80.4Hurt

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