Research map / 3D vision / Face and shape
Inextensible Non-Rigid Shape-From-Motion by Second-Order Cone Programming
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use perspective-camera inextensibility with MDH rather than low-rank factorization | NRSfM reconstruction · Hulk | mean depth error: 3.5 mm vs 14.53 mm | Helped |
| Use perspective-camera inextensibility with MDH rather than low-rank factorization | NRSfM reconstruction · T-Shirt | mean depth error: 4.9 mm vs 8.94 mm | Helped |
| Use perspective-camera inextensibility with MDH rather than low-rank factorization | NRSfM reconstruction · Stepping Trousers | 3D RMSE: 22.54 mm vs 51.5 mm | Helped |
| Use perspective-camera inextensibility with MDH rather than low-rank factorization | NRSfM reconstruction · Stepping Trousers | % 3D error: 2.37% vs 11.56% | Helped |
| Use perspective-camera inextensibility with MDH rather than low-rank factorization | NRSfM reconstruction · Hand | 3D RMSE: 7.38 mm vs 63.66 mm | Helped |
| Reconstruct with tlmdh rather than competing methods | NRSfM reconstruction · Flag | 3D RMSE: 6.3 mm | Helped |
Closest papers by meaning
- Isometric Non-Rigid Shape-From-Motion in Linear Time (CVPR 2016 · similarity 0.89)
- KillingFusion: Non-Rigid 3D Reconstruction Without Correspondences (CVPR 2017 · similarity 0.89)
- Local Non-Rigid Structure-From-Motion From Diffeomorphic Mappings (CVPR 2020 · similarity 0.88)
- Non-Rigid Structure-from-Motion: Temporally-Smooth Procrustean Alignment and Spatially-Variant Deformation Modeling (CVPR 2024 · similarity 0.86)
- Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstruction (CVPR 2024 · similarity 0.86)
- Deep Non-Rigid Structure-from-Motion Revisited: Canonicalization and Sequence Modeling (AAAI 2025 · similarity 0.85)
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