Research map / Point clouds / Registration and matching
RPM-Net: Robust Point Matching Using Learned Features
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use learned hybrid features and Sinkhorn-based outlier handling | RPM-Net · ModelNet40 Gaussian noise | isotropic rotation error: 0.664 vs 2.926 | Helped |
| Use learned hybrid features and Sinkhorn-based outlier handling | RPM-Net · ModelNet40 partial visibility with noise | isotropic rotation error: 1.712 vs 6.380 | Helped |
| Remove PPF features (ablation) | RPM-Net · ModelNet40 partial visibility with noise | isotropic rotation error: 1.712 -> 3.302 | Hurt |
| Remove local neighbor coordinates Δx (ablation) | RPM-Net · ModelNet40 partial visibility with noise | isotropic rotation error: 1.712 -> 2.781 | Hurt |
| Remove absolute centroid coordinates x (ablation) | RPM-Net · ModelNet40 partial visibility with noise | isotropic rotation error: 1.712 -> 5.501 | Hurt |
| Replace per-iteration parameter prediction with fixed learned α and β (ablation) | RPM-Net · ModelNet40 partial visibility with noise | isotropic rotation error: 1.712 -> 2.220 | Hurt |
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