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Distribution-Aware Coordinate Representation for Human Pose Estimation

CVPR 2020 · 3D vision › Human pose estimation · approach: Heatmap and coordinate pose encoding · 561 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace standard shifting with Taylor-based distribution-aware decodingHRNet-W32 · COCO val2017, 128×96AP: 66.9 -> 68.4Helped
Add the standard 0.25-pixel shift instead of using the maximum activation directly (ablation)HRNet-W32 · COCO val2017, 128×96AP: 61.2 -> 66.9Helped
Add Gaussian distribution modulation before DARK decoding (ablation)DARK decoder on HRNet-W32 · COCO val2017, 128×96AP: 68.1 -> 68.4Helped
Use sub-pixel ground-truth heatmap centers instead of quantized centers (ablation)HRNet-W32 with standard decoding · COCO val2017, 128×96AP: 66.9 -> 68.0Helped
Use sub-pixel ground-truth heatmap centers instead of quantized centers (ablation)HRNet-W32 with DARK decoding · COCO val2017, 128×96AP: 68.4 -> 70.7Helped
Add DARK representation to HRNet-W48HRNet-W48 · COCO test-dev2017AP: 75.5 -> 76.2Helped
Add DARK representation to HRNet-W32HRNet-W32 · MPII validationPCKh@0.1 Mean: 37.7 -> 42.0Helped
Add DARK representation to HRNet-W32 at reduced input resolutionHRNet-W32 · COCO val2017, 128×96AP: 66.9 -> 70.7Helped

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