Point Cloud Classification on ModelNet40 v1.0 (Random)
90.5AccuracyART-DGCNN
Evaluation Results
| Method | Links | |
|---|---|---|
| ART-DGCNNModel Category=Adversarial Rotation Training2022.03 | 90.5 | |
| VN-DGCNNModel Category=Equivariant Architectures2022.03 | 90.2 | |
| SFCNNModel Category=Invariant Descriptors2022.03 | 90.1 | |
| RI-FrameworkModel Category=Invariant Descriptors2022.03 | 89.3 | |
| EPNModel Category=Equivariant Architectures2022.03 | 88.3 | |
| TFNModel Category=Equivariant Architectures2022.03 | 87.6 | |
| ART-PointNet++Model Category=Adversarial Rotation Training2022.03 | 87.5 | |
| ClusterNetModel Category=Invariant Descriptors2022.03 | 87.1 | |
| RI-ConvModel Category=Invariant Descriptors2022.03 | 86.4 | |
| ART-PointNetModel Category=Adversarial Rotation Training2022.03 | 84.3 | |
| VN-PointNetModel Category=Equivariant Architectures2022.03 | 77.2 | |
| REQNNModel Category=Equivariant Architectures2022.03 | 74.1 |