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Beyond Static Features for Temporally Consistent 3D Human Pose and Shape From a Video

CVPR 2021 · 3D vision › Human pose estimation · approach: Temporal video pose estimation · 257 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Remove the residual connection between static and temporal features (ablation)VIBE-style temporal baseline · 3DPWAccel: 29.2 -> 8.7Helped
Add PoseForecast to encode past and future frames (ablation)VIBE-style temporal baseline · 3DPWAccel: 29.2 -> 24.9; 8.7 -> 7.7Helped
Exclude the current frame from PoseForecast input (ablation)TCMR · 3DPWAccel: 10.3 -> 7.7Helped
Supervise PoseForecast SMPL parameters with current-frame ground truth (ablation)TCMR · 3DPWPA-MPJPE: 55.1 -> 53.9; 54.1 -> 53.9Helped
Supervise PoseForecast with past and future frame ground truth instead of current-frame ground truth (ablation)TCMR · 3DPWAccel: 7.7 -> 8.5Hurt
Remove PoseForecast SMPL-parameter supervision (ablation)TCMR · 3DPWPA-MPJPE: 53.9 -> 55.1Hurt
Add average filtering post-processing (ablation)TCMR · 3DPWPA-MPJPE: 52.7 -> 55.0Hurt
Reduce the input frame rate from 30 fps to 15 fps (ablation)TCMR · 3DPWAccel: 7.1 -> 15.3Hurt
Use TCMR instead of MEVAvideo-based 3D pose and shape estimation · 3DPWAccel: 11.6 -> 6.8Helped
Use TCMR instead of MEVAvideo-based 3D pose and shape estimation · MPI-INF-3DHPAccel: 11.1 -> 8.5Helped
Use TCMR instead of MEVAvideo-based 3D pose and shape estimation · Human3.6MAccel: 15.3 -> 3.9Helped

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