Research map / 3D vision / Human pose estimation
End-to-End Recovery of Human Shape and Pose
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add paired 2D-to-3D supervision during training (ablation) | HMR · Human3.6M Protocol 2 | Reconstruction error (mm): 66.5 -> 56.8 | Helped |
| add paired 2D-to-3D supervision during training (ablation) | HMR · Human3.6M Protocol 1 | MPJPE (mm): 106.84 -> 87.97 | Helped |
| add paired 2D-to-3D supervision during training (ablation) | HMR · MPI-INF-3DHP test | MPJPE (mm): 169.5 -> 124.2 | Helped |
| add paired 2D-to-3D supervision during training (ablation) | HMR · LSP test | Part segmentation F1: 0.59 -> 0.60 | Helped |
| remove the adversarial prior (ablation) | HMR trained without paired 3D supervision · Single-image human mesh reconstruction | Body plausibility | Hurt |
| factorize the adversarial prior across shape, individual joint rotations, and whole-body pose | HMR · Human mesh reconstruction | Body plausibility | Helped |
Closest papers by meaning
- GenHMR: Generative Human Mesh Recovery (AAAI 2025 · similarity 0.91)
- FactorizedHMR: A Hybrid Framework for Video Human Mesh Recovery (NeurIPS 2026 · similarity 0.91)
- Self-Supervised 3D Human Mesh Recovery from a Single Image with Uncertainty-Aware Learning (AAAI 2024 · similarity 0.90)
- PostureHMR: Posture Transformation for 3D Human Mesh Recovery (CVPR 2024 · similarity 0.90)
- MEGA: Masked Generative Autoencoder for Human Mesh Recovery (CVPR 2025 · similarity 0.90)
- TokenHMR: Advancing Human Mesh Recovery with a Tokenized Pose Representation (CVPR 2024 · similarity 0.90)
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