Supervised Only 3D Point Cloud Classification
Metriken
Number of params (M)
Overall Accuracy (PB_T50_RS)
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Number of params (M) | Overall Accuracy (PB_T50_RS) |
|---|---|---|
| parameter-is-not-all-you-need-starting-from | 0.8 | 87.1 |
| pointnet-deep-learning-on-point-sets-for-3d | 3.5 | 68.0 |
| mamba3d-enhancing-local-features-for-3d-point | 16.9 | 92.64 |
| point-could-mamba-point-cloud-learning-via | 34.2 | 88.1 |
| decoupled-local-aggregation-for-point-cloud | 5.3 | 90.4 |
| self-positioning-point-based-transformer-for | 1.7 | 88.6 |
| dynamic-graph-cnn-for-learning-on-point | 1.8 | 78.1 |
| attention-is-all-you-need | 22.1 | 77.24 |
| rethinking-network-design-and-local-geometry-1 | 12.6 | 85.4 |
| pointnet-deep-hierarchical-feature-learning | 1.5 | 77.9 |
| mamba3d-enhancing-local-features-for-3d-point | 16.9 | 91.81 |
| pointnext-revisiting-pointnet-with-improved | 1.4 | 87.8 |