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Global-to-Local Modeling for Video-Based 3D Human Pose and Shape Estimation

CVPR 2023 · 3D vision › Human pose estimation · approach: Temporal video pose estimation · 79 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace single coupled temporal modeling with global-to-local modelingGLoT · 3DPWPA-MPJPE: 52.1 -> 50.6Helped
Replace single coupled temporal modeling with global-to-local modelingGLoT · MPI-INF-3DHPMPJPE: 96.7 -> 93.9Helped
Replace single coupled temporal modeling with global-to-local modelingGLoT · Human3.6MPA-MPJPE: 47.4 -> 46.3Helped
Add Local Parameter Correction to Global Motion Modeling (ablation)GLoT · 3DPWPA-MPJPE: 52.6 -> 50.6Helped
Use masked pose and shape estimation rather than no masking (ablation)GLoT · 3DPWMPJPE: 82.3 -> 80.7Helped
Increase masking to 87.5% rather than 0% (ablation)GLoT · 3DPWAccel: 7.3 -> 6.5Helped
Increase masking to 87.5% rather than 0% (ablation)GLoT · 3DPWPA-MPJPE: 51.7 -> 52.8Hurt
Use an SMPL mean-template mask token instead of a learnable token (ablation)GLoT · 3DPWPA-MPJPE: 51.5 -> 50.6Helped
Use HSCR instead of a residual connection (ablation)GLoT · 3DPWMPJPE: 81.7 -> 80.7Helped
Set nearby-frame length to 4 rather than 2 (ablation)GLoT · 3DPWPA-MPJPE: 51.9 -> 50.6Helped
Set nearby-frame length to 4 rather than 2 (ablation)GLoT · 3DPWMPJPE: 83 -> 80.7Mixed
Detach the global-estimation gradient path into HSCR (ablation)GLoT · 3DPWPA-MPJPE: 50.9 -> 50.6Helped

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