Research map / Point clouds / Shape and surface completion
Medial Spectral Coordinates for 3D Shape Analysis
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use AOF medial surfaces instead of medial curves for reconstruction | 3D shape reconstruction · COSEG | mIoU: 75.49 -> 94.89 | Helped |
| Use AOF medial surfaces instead of medial curves for reconstruction | 3D shape reconstruction · ModelNet10 | mIoU: 82.43 -> 94.25 | Helped |
| Add medial radius information to spectral coordinates (ablation) | SpectralMedial segmentation · Princeton segmentation benchmark | Rand Index (error): 0.1273 -> 0.0696 | Helped |
| Add medial spectral features to point features | PointNet · ModelNet-10 | accuracy: 88.76% -> 90.41% | Helped |
| Add medial spectral features to point features | PointNet · ModelNet-40 | accuracy: 86.23% -> 88.26% | Helped |
| Use medially driven spectral coordinates rather than conformal methods | MedialSpectral correspondence · TOSCA | correspondence accuracy | Helped |
Closest papers by meaning
- Spectral Meets Spatial: Harmonising 3D Shape Matching and Interpolation (CVPR 2024 · similarity 0.88)
- From Feature Learning to Spectral Basis Learning: A Unifying and Flexible Framework for Efficient and Robust Shape Matching (CVPR 2026 · similarity 0.87)
- A Robust Local Spectral Descriptor for Matching Non-Rigid Shapes With Incompatible Shape Structures (CVPR 2019 · similarity 0.87)
- Learning Eigenstructures of Unstructured Data Manifolds (CVPR 2026 · similarity 0.86)
- Coupled Laplacian Eigenmaps for Locally-Aware 3D Rigid Point Cloud Matching (CVPR 2024 · similarity 0.85)
- Dynamic Neural Surfaces for Elastic 4D Shape Representation and Analysis (CVPR 2025 · similarity 0.84)
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