Research map / 3D vision / Face and shape
Unsupervised Learning of 3D Object Categories From Videos in the Wild
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use WCR rather than global image embeddings | 3D object-category reconstruction · AMT Objects test | ℓ1 RGB: 0.09 -> 0.05 | Helped |
| Use WCR rather than global image embeddings | 3D object-category reconstruction · AMT Objects test | IoU: 0.66 -> 0.83 | Helped |
| Use WCR rather than global image embeddings | 3D object-category reconstruction · Freiburg Cars test | ℓ1 RGB: 0.15 -> 0.12 | Helped |
| Use WCR rather than global image embeddings | 3D object-category reconstruction · Freiburg Cars test | ℓ1 Depth: 1.06 -> 1.60 | Hurt |
| Increase the number of source views from 1 to 7 (ablation) | Ours · AMT Objects test | ℓ1 RGB: .058 -> .042 | Helped |
| Increase test-time source views (ablation) | Ours · AMT Objects and Freiburg Cars | ℓ1 RGB | Helped |
| Increase test-time source views (ablation) | Mesh, Voxel, Voxel+MLP, and MLP · AMT Objects and Freiburg Cars | ℓ1 RGB | No clear effect |
Closest papers by meaning
- Pre-Train, Self-Train, Distill: A Simple Recipe for Supersizing 3D Reconstruction (CVPR 2022 · similarity 0.90)
- Learning Monocular 3D Reconstruction of Articulated Categories From Motion (CVPR 2021 · similarity 0.89)
- Unsupervised Learning of Category-Level 3D Pose from Object-Centric Videos (CVPR 2024 · similarity 0.89)
- Learning Implicit Representation for Reconstructing Articulated Objects (ICLR 2024 · similarity 0.87)
- Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature Space (CVPR 2025 · similarity 0.87)
- RGBD Objects in the Wild: Scaling Real-World 3D Object Learning from RGB-D Videos (CVPR 2024 · similarity 0.87)
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