Point Cloud Registration On 3Dmatch Trained
Metrics
Recall
Results
Performance results of various models on this benchmark
Model Name | Recall | Paper Title | Repository |
|---|---|---|---|
| D3Feat-pred | 0.627 | D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features | |
| SpinNet | 0.845 | SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration | |
| FPFH | 0.136 | Fast Point Feature Histograms (FPFH) for 3D Registration | |
| GeDi | 0.922 | Learning general and distinctive 3D local deep descriptors for point cloud registration | |
| FCGF | 0.325 | Fully Convolutional Geometric Features |
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