Research map / 3D vision / Human pose estimation
Coherent Reconstruction of Multiple Humans From a Single Image
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add interpenetration and depth ordering-aware losses | Top-down SMPL regression (Ours baseline) · Panoptic Mean | Mean per joint position error: 149.8 -> 143.2 | Helped |
| Add interpenetration and depth ordering-aware losses | Top-down SMPL regression (Ours baseline) · MuPoTS-3D All | 3DPCK: 66.95 -> 69.12 | Helped |
| Add interpenetration and depth ordering-aware losses | Top-down SMPL regression (Ours baseline) · MuPoTS-3D Matched | 3DPCK: 68.96 -> 72.22 | Helped |
| Add the interpenetration loss (ablation) | Top-down SMPL regression · MuPoTS-3D | Number of collisions: 114 -> 34 | Helped |
| Add the interpenetration loss (ablation) | Top-down SMPL regression · PoseTrack | Number of collisions: 653 -> 202 | Helped |
| Add the depth ordering-aware loss (ablation) | Top-down SMPL regression · MuPoTS-3D | Ordinal depth relation accuracy: 92.17% -> 93.68% | Helped |
Closest papers by meaning
- Multi-Person Implicit Reconstruction From a Single Image (CVPR 2021 · similarity 0.91)
- Monocular 3D Pose and Shape Estimation of Multiple People in Natural Scenes - The Importance of Multiple Scene Constraints (CVPR 2018 · similarity 0.90)
- MultiPly: Reconstruction of Multiple People from Monocular Video in the Wild (CVPR 2024 · similarity 0.89)
- ODHSR: Online Dense 3D Reconstruction of Humans and Scenes from Monocular Videos (CVPR 2025 · similarity 0.89)
- Reconstructing People, Places, and Cameras (CVPR 2025 · similarity 0.88)
- Guess The Unseen: Dynamic 3D Scene Reconstruction from Partial 2D Glimpses (CVPR 2024 · similarity 0.87)
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