3D Object Classification on ScanNet 10
65.9AccuracyNFNNP
Evaluation results
| Method | Links | |
|---|---|---|
| NFNNP2023.02 | 65.9 | |
| NFNHNP2023.02 | 64.1 | |
| MLPData Augmentation=Permutation2023.02 | 45.5 | |
| inr2vec2023.02 | 38.2 | |
| MLPData Augmentation=None2023.02 | 32.9 | |
| Primitive3DPre-training supervision=Uns&Sup2022.05 | 0.729 | |
| ShapeNetPre-training supervision=Uns2022.05 | 0.723 | |
| Primitive3DPre-training supervision=Sup2022.05 | 0.72 | |
| ModelNet40Pre-training supervision=Uns2022.05 | 0.719 | |
| ModelNet40Pre-training supervision=Uns&Sup2022.05 | 0.7 | |
| Primitive3DPre-training supervision=Uns2022.05 | 0.7 | |
| ShapeNetPre-training supervision=Uns&Sup2022.05 | 0.693 | |
| ScanObjectNNPre-training supervision=Uns&Sup2022.05 | 0.68 | |
| ScanObjectNNPre-training supervision=Uns2022.05 | 0.674 | |
| ShapeNetPre-training supervision=Sup2022.05 | 0.663 | |
| ModelNet40Pre-training supervision=Sup2022.05 | 0.644 | |
| ScanObjectNNPre-training supervision=Sup2022.05 | 0.62 |