3D Object Classification on ModelNet 1k points 40 (test)
94.3AccuracyPoint-SRA
Evaluation results
| Method | Links | |
|---|---|---|
| Point-SRALearning Paradigm=Cross-Modal Self-Supervised Representation Learning2026.01 | 94.3 | |
| ReConLearning Paradigm=Cross-Modal Self-Supervised Representation Learning2026.01 | 94.1 | |
| PointNeXtLearning Paradigm=Supervised Learning Only2026.01 | 94 | |
| P2PLearning Paradigm=Supervised Learning Only2026.01 | 94 | |
| Point-M2AELearning Paradigm=Single-Modal Self-Supervised Representation Learning2026.01 | 94 | |
| Point-FEMAELearning Paradigm=Single-Modal Self-Supervised Representation Learning2026.01 | 94 | |
| Point-MAELearning Paradigm=Single-Modal Self-Supervised Representation Learning2026.01 | 93.8 | |
| Point-JEPALearning Paradigm=Single-Modal Self-Supervised Representation Learning2026.01 | 93.8 | |
| ACTLearning Paradigm=Cross-Modal Self-Supervised Representation Learning2026.01 | 93.7 | |
| I2P-MAELearning Paradigm=Cross-Modal Self-Supervised Representation Learning2026.01 | 93.7 | |
| Point-BERTLearning Paradigm=Single-Modal Self-Supervised Representation Learning2026.01 | 93.2 | |
| PCTLearning Paradigm=Supervised Learning2025.12 | 93.2 | |
| PointDicoLearning Paradigm=Diffusion-based SSL, Voting Strategy=true2025.12 | 92.4 | |
| PointNet++Learning Paradigm=Supervised Learning Only2026.01 | 90.7 | |
| PointNetLearning Paradigm=Supervised Learning Only2026.01 | 89.2 |