3D Classification on ScanObjectNN PB-T50-RS official
93.87AccuracyHybridNet
Evaluation Results
| Method | Links | |
|---|---|---|
| HybridNetPT=MAP, #P=19.3, #F=4.4, Voting Strategy=w/ vot.2024.10 | 93.87 | |
| Mamba3dPT=MAP, #P=16.9, #F=3.9, Voting Strategy=w/ vot.2024.10 | 93.76 | |
| Mamba3dPT=Point-MAE, #P=16.9, #F=3.9, Voting Strategy=w/ vot.2024.10 | 93.05 | |
| HybridNetPT=MAP, #P=19.3, #F=4.4, Voting Strategy=w/o vot.2024.10 | 92.95 | |
| HybridNetPT=None, #P=19.3, #F=4.4, Voting Strategy=w/ vot.2024.10 | 92.66 | |
| Mamba3dPT=MAP, #P=16.9, #F=3.9, Voting Strategy=w/o vot.2024.10 | 92.65 | |
| Mamba3dPT=None, #P=16.9, #F=3.9, Voting Strategy=w/ vot.2024.10 | 92.64 | |
| Mamba3dPT=Point-MAE, #P=16.9, #F=3.9, Voting Strategy=w/o vot.2024.10 | 92.05 | |
| HybridNetPT=None, #P=19.3, #F=4.4, Voting Strategy=w/o vot.2024.10 | 91.97 | |
| Mamba3dPT=None, #P=16.9, #F=3.9, Voting Strategy=w/o vot.2024.10 | 91.81 | |
| Point-RAEEvaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 90.28 | |
| I2P-MAEYear=2023, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 90.11 | |
| Mamba3dPT=Point-BERT, #P=16.9, #F=3.9, Voting Strategy=w/o vot.2024.10 | 90.11 | |
| P2P-HorNetYear=2022, Evaluation Protocol=Supervised Learning Only2023.09 | 89.3 | |
| ACTYear=2023, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 88.21 | |
| P2P-RN101Year=2022, Evaluation Protocol=Supervised Learning Only2023.09 | 87.4 | |
| Point-M2AEYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 86.43 | |
| Point-M2AEPT=Point-M2AE, #P=15.3, #F=3.62024.10 | 86.43 | |
| Point-MAEYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 85.18 | |
| TransformerPT=Point-MAE, #P=22.1, #F=4.82024.10 | 85.18 | |
| TransformerPT=Point-MAE, #P=22.1+1.7, #F=4.82024.10 | 84.94 | |
| PointMambaPT=Point-MAE, #P=12.3, #F=3.62024.10 | 84.87 | |
| MaskPointYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 84.3 | |
| TransformerPT=MaskPoint, #P=22.1, #F=4.82024.10 | 84.3 | |
| TransformerPT=Point-BERT, #P=22.1+1.7, #F=4.82024.10 | 83.69 | |
| Point-BERTYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 83.07 | |
| MVTNYear=2021, Evaluation Protocol=Supervised Learning Only2023.09 | 82.8 | |
| MVTNPT=None, #P=11.2, #F=43.72024.10 | 82.8 | |
| PointMambaPT=None, #P=12.3, #F=3.62024.10 | 82.48 | |
| GBNetYear=2021, Evaluation Protocol=Supervised Learning Only2023.09 | 81 | |
| PRA-NetYear=2021, Evaluation Protocol=Supervised Learning Only2023.09 | 81 | |
| TransformerPT=OcCo, #P=22.1, #F=4.82024.10 | 78.79 | |
| PointCNNYear=2018, Evaluation Protocol=Supervised Learning Only2023.09 | 78.5 | |
| PointCNNPT=None, #P=0.62024.10 | 78.5 | |
| DGCNNYear=2019, Evaluation Protocol=Supervised Learning Only2023.09 | 78.1 | |
| DGCNNPT=None, #P=1.8, #F=2.42024.10 | 78.1 | |
| PointNet++Year=2017, Evaluation Protocol=Supervised Learning Only2023.09 | 77.9 | |
| PointNet++PT=None, #P=1.5, #F=1.72024.10 | 77.9 | |
| TransformerYear=2017, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 77.24 | |
| TransformerPT=None, #P=22.1, #F=4.82024.10 | 77.24 | |
| PointNetYear=2016, Evaluation Protocol=Supervised Learning Only2023.09 | 68 | |
| PointNetPT=None, #P=3.5, #F=0.52024.10 | 68 |