Unsupervised 3D Semantic Segmentation
2 papers with code • 1 benchmarks • 1 datasets
Unsupervised 3D Semantic Segmentation
Benchmarks
These leaderboards are used to track progress in Unsupervised 3D Semantic Segmentation
| Trend | Dataset | Best Model | Paper | Code | Compare |
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ScanNet
Most implemented papers
SL3D: Self-supervised-Self-labeled 3D Recognition
fcendra/sl3d
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SL3D is a generic framework and can be applied to solve different 3D recognition tasks, including classification, object detection, and semantic segmentation.
Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color Contrast
Geometry and color information provided by the point clouds are both crucial for 3D scene understanding.
