Object Classification on ModelNet40 (Voting Variants)
94.1Accuracy (No Vote)MPL-MAE
Evaluation results
| Method | Links | ||
|---|---|---|---|
| MPL-MAE#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2026.06 | 94.1 | 94.4 | |
| Point-FEMAE#P (M)=27.4, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2026.06 | 94 | 94.5 | |
| PCP-MAE#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2026.06 | 94 | 94.2 | |
| Point-M2AE#P (M)=15.3, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2026.06 | 93.4 | 94 | |
| Point-MAE#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2026.06 | 93.2 | 93.8 | |
| Point-MAE†#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2026.06 | 93.2 | 93.5 | |
| MPL-MAE#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-3)2026.06 | 93 | 93.6 | |
| DGCNN#P (M)=1.8, Input=1K Points, Evaluation Protocol=Supervised Learning Only2026.06 | 92.9 | — | |
| MPL-MAE#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-LINEAR)2026.06 | 92.9 | 93.2 | |
| Point-PQAE#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-3)2026.06 | 92.9 | 92.9 | |
| PCP-MAE#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-3)2026.06 | 92.9 | 93.3 | |
| Point-BERT#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2026.06 | 92.7 | 93.2 | |
| Point-FEMAE#P (M)=27.4, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-3)2026.06 | 92.6 | 93 | |
| PCP-MAE#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-LINEAR)2026.06 | 92.3 | 93.1 | |
| Point-PQAE#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-LINEAR)2026.06 | 92.2 | 92.8 | |
| Point-FEMAE#P (M)=27.4, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-LINEAR)2026.06 | 92.1 | 92 | |
| Point-MAE†#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-3)2026.06 | 91.8 | 92 | |
| PointNet++#P (M)=1.5, Input=1K Points, Evaluation Protocol=Supervised Learning Only2026.06 | 90.7 | — | |
| Point-MAE†#P (M)=22.1, Input=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (MLP-LINEAR)2026.06 | 90.6 | 91.2 | |
| PointNet#P (M)=3.5, Input=1K Points, Evaluation Protocol=Supervised Learning Only2026.06 | 89.2 | — | |
| MaskPointInput=1K Points, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2026.06 | — | 93.8 |