3D Classification on ScanObjectNN OBJ-ONLY official
93.63AccuracyPoint-RAE
Evaluation Results
| Method | Links | |
|---|---|---|
| Point-RAEEvaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 93.63 | |
| MVTNYear=2021, Evaluation Protocol=Supervised Learning Only2023.09 | 92.3 | |
| ACTYear=2023, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 91.91 | |
| I2P-MAEYear=2023, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 91.57 | |
| Point-M2AEYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 88.81 | |
| Point-MAEYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 88.29 | |
| Point-BERTYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 88.12 | |
| MaskPointYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 88.1 | |
| DGCNNYear=2019, Evaluation Protocol=Supervised Learning Only2023.09 | 86.2 | |
| PointCNNYear=2018, Evaluation Protocol=Supervised Learning Only2023.09 | 85.5 | |
| PointNet++Year=2017, Evaluation Protocol=Supervised Learning Only2023.09 | 84.3 | |
| TransformerYear=2017, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.09 | 80.55 | |
| PointNetYear=2016, Evaluation Protocol=Supervised Learning Only2023.09 | 79.2 |