Research map / Point clouds / Point cloud classification
Contour Detection in Unstructured 3D Point Clouds
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the proposed two-stage contour detector instead of 3D Canny edge detection on a range image | Outdoor point-cloud contour detection · Outdoor laser scan test set | F1-score | Helped |
| Use the full multiscale feature set instead of curvature features alone (ablation) | Pointwise contour classification · Hand-labeled outdoor scan test set | precision-recall | Helped |
| Use multiscale rather than single-scale curvature and occlusion features (ablation) | Pointwise contour classification · Hand-labeled outdoor scan test set | precision-recall | Helped |
| Add occlusion features to multiscale curvature features (ablation) | Pointwise contour classification · Hand-labeled outdoor scan test set | precision-recall | Helped |
| Add cumulative shape-context features to aggregated pointwise scores (ablation) | Linewise contour classification · Outdoor scan test set | precision-recall | Helped |
Closest papers by meaning
- FreePoint: Unsupervised Point Cloud Instance Segmentation (CVPR 2024 · similarity 0.88)
- PointCFormer: A Relation-Based Progressive Feature Extraction Network for Point Cloud Completion (AAAI 2025 · similarity 0.87)
- CurveCloudNet: Processing Point Clouds with 1D Structure (CVPR 2024 · similarity 0.86)
- Digging into Intrinsic Contextual Information for High-fidelity 3D Point Cloud Completion (AAAI 2025 · similarity 0.86)
- STAR-Edge: Structure-aware Local Spherical Curve Representation for Thin-walled Edge Extraction from Unstructured Point Clouds (CVPR 2025 · similarity 0.86)
- Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration (NeurIPS 2024 · similarity 0.86)
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