Point Cloud Classification on ModelNet40 Clean v1.0
91.3AccuracyART-DGCNN
Evaluation results
| Method | Links | |
|---|---|---|
| ART-DGCNNModel Category=Adversarial Rotation Training2022.03 | 91.3 | |
| VN-DGCNNModel Category=Equivariant Architectures2022.03 | 90.2 | |
| SFCNNModel Category=Invariant Descriptors2022.03 | 90.1 | |
| RI-FrameworkModel Category=Invariant Descriptors2022.03 | 89.4 | |
| ART-PointNet++Model Category=Adversarial Rotation Training2022.03 | 88.6 | |
| EPNModel Category=Equivariant Architectures2022.03 | 88.3 | |
| TFNModel Category=Equivariant Architectures2022.03 | 87.6 | |
| ClusterNetModel Category=Invariant Descriptors2022.03 | 87.1 | |
| RI-ConvModel Category=Invariant Descriptors2022.03 | 86.5 | |
| ART-PointNetModel Category=Adversarial Rotation Training2022.03 | 85.5 | |
| VN-PointNetModel Category=Equivariant Architectures2022.03 | 77.2 | |
| REQNNModel Category=Equivariant Architectures2022.03 | 74.4 |