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Deformable Mesh Transformer for 3D Human Mesh Recovery

CVPR 2023 · 3D vision › Human pose estimation · approach: Human mesh recovery from images · 35 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use DeFormer with HRNet-w48 instead of FastMETRO3DPW · 3DPWMPVE: 84.1 -> 82.6Helped
Use DeFormer with HRNet-w48 instead of FastMETRO3DPW · 3DPWMPJPE: 73.5 -> 72.9Helped
Use DeFormer with HRNet-w48 instead of FastMETRO3DPW · 3DPWPA-MPJPE: 44.6 -> 44.3Helped
Use DeFormer with HRNet-w48 instead of FastMETROHuman3.6M P2 · Human3.6M P2MPJPE: 33.7 -> 31.6Helped
Use four HRNet feature-map scales rather than only W4 (ablation)DeFormer with HRNet-w48-COCO · Human3.6MMPJPE: 50.9 -> 44.8Helped
Use four HRNet feature-map scales rather than only W4 (ablation)DeFormer with HRNet-w48-COCO · Human3.6MPA-MPJPE: 36.5 -> 31.6Helped
Use four ResNet50 feature-map scales rather than only W4 (ablation)DeFormer with ResNet50-COCO · Human3.6MMPJPE: 50.5 -> 50.7Mixed
Replace MS deformable cross-attention with bilinear interpolation (ablation)DeFormer · Human3.6MMPJPE: 44.8 -> 48.3Hurt
Replace MS deformable cross-attention with standard transformer cross-attention (ablation)DeFormer · Human3.6MMPJPE: 44.8 -> 50.7Hurt
Use three MS deformable cross-attention layers instead of one (ablation)DeFormer · Human3.6MMPJPE: 47.7 -> 44.8Helped
Replace MS deformable cross-attention with bilinear interpolation (ablation)DeFormer · Human3.6MPA-MPJPE: 31.6 -> 34.3Hurt
Replace MS deformable cross-attention with standard transformer cross-attention (ablation)DeFormer · Human3.6MPA-MPJPE: 31.6 -> 37.1Hurt

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