Point Cloud Classification on ScanObjectNN OBJ-ONLY
92.75Overall AccuracyPoint-MAE w/ LCM
Evaluation Results
| Method | Links | |
|---|---|---|
| Point-MAE w/ LCMPretrain=MPM, #Params(M)=2.7, FLOPs(G)=1.32024.05 | 92.75 | |
| ACT w/ LCMPretrain=MPM, #Params(M)=3.1, FLOPs(G)=2.82024.05 | 92.66 | |
| PointGPT-BPretrain=GPT, #Params(M)=120.5, FLOPs(G)=36.2, Evaluation Setting=Original Paper2024.05 | 92.5 | |
| Point-BERT w/ LCMPretrain=MPM, #Params(M)=3.1, FLOPs(G)=2.52024.05 | 92.43 | |
| Point-M2AE w/ LCMPretrain=MPM, #Params(M)=2.5, FLOPs(G)=6.72024.05 | 92.41 | |
| Point-MAEPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Reproduced downstream setting2024.05 | 92.08 | |
| MaskPoint w/ LCMPretrain=MPM, #Params(M)=3.1, FLOPs(G)=2.52024.05 | 91.98 | |
| ACTPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Original Paper2024.05 | 91.91 | |
| PointMambaPretrain=MPM, #Params(M)=12.3, Evaluation Setting=Original Paper2024.05 | 91.91 | |
| ACTPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Reproduced downstream setting2024.05 | 91.7 | |
| MaskPointPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.5, Evaluation Setting=Reproduced downstream setting2024.05 | 91.69 | |
| Point-BERTPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.5, Evaluation Setting=Reproduced downstream setting2024.05 | 91.6 | |
| LCMPretrain=X, #Params(M)=2.7, FLOPs(G)=1.32024.05 | 91.54 | |
| TransformerPretrain=X, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Reproduced downstream setting2024.05 | 91.39 | |
| Point-M2AEPretrain=MPM, #Params(M)=12.9, FLOPs(G)=7.9, Evaluation Setting=Reproduced downstream setting2024.05 | 91.22 | |
| Point-MAE w/ DAPTPretrain=MPM, #Params(M)=22.7, FLOPs(G)=5.0, Evaluation Setting=Original Paper2024.05 | 90.19 | |
| ExpPoint-MAEunfreeze epoch=2502023.06 | 90.02 | |
| Point-MAE w/ IDPTPretrain=MPM, #Params(M)=23.3, FLOPs(G)=7.1, Evaluation Setting=Original Paper2024.05 | 90.02 | |
| MaskFeat3DBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 90 | |
| MaskPoint2023.06 | 89.7 | |
| ExpPoint-MAEextra domain adaptation pretraining=true2023.06 | 89.67 | |
| Inter-MAEPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Original Paper2024.05 | 89.6 | |
| ExpPoint-MAEunfreeze epoch=2002023.06 | 89.33 | |
| MaskDiscrBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 89.3 | |
| MaskSurfelBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 89.2 | |
| Point-M2AE2023.06 | 88.81 | |
| Point-M2AEPretrain=MPM, #Params(M)=12.9, FLOPs(G)=7.9, Evaluation Setting=Original Paper2024.05 | 88.81 | |
| PointMAEBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 88.3 | |
| Point-MAE2023.06 | 88.29 | |
| Point-MAEPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Original Paper2024.05 | 88.29 | |
| Point-BERT2023.06 | 88.12 | |
| Point-BERTPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.5, Evaluation Setting=Original Paper2024.05 | 88.12 | |
| MaskPointPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.5, Evaluation Setting=Original Paper2024.05 | 88.1 | |
| PointBERTBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 88.1 | |
| PointMambaPretrain=X, #Params(M)=12.3, Evaluation Setting=Original Paper2024.05 | 87.78 | |
| TransformerPretrain=X, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Original Paper2024.05 | 86.92 | |
| Foundrys=16, Frozen student=false2025.11 | 86.29 | |
| PointNet++Pretrain=X, #Params(M)=1.5, FLOPs(G)=1.7, Evaluation Setting=Original Paper2024.05 | 84.3 | |
| PointViTBackbone=PointViT, Evaluation Protocol=from scratch2025.12 | 80.6 | |
| PointNetPretrain=X, #Params(M)=3.5, FLOPs(G)=0.5, Evaluation Setting=Original Paper2024.05 | 79.2 | |
| Point-FEMAELearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=27.4, Input Data=2k Points2023.12 | 0.9329 | |
| ReconLearning Paradigm=Cross-Modal Self-Supervised Learning, #Params (M)=44.3, Input Data=2k Points2023.12 | 0.9329 | |
| ACTLearning Paradigm=Cross-Modal Self-Supervised Learning, #Params (M)=22.1, Input Data=2k Points2023.12 | 0.9191 | |
| I2P-MAELearning Paradigm=Cross-Modal Self-Supervised Learning, #Params (M)=15.3, Input Data=2k Points2023.12 | 0.9157 | |
| Joint-MAELearning Paradigm=Cross-Modal Self-Supervised Learning, Input Data=2k Points2023.12 | 0.8886 | |
| Point-M2AELearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=15.3, Input Data=2k Points2023.12 | 0.8881 | |
| Point-MAELearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=22.1, Input Data=2k Points2023.12 | 0.8829 | |
| Point-BERTLearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=22.1, Input Data=1k Points2023.12 | 0.8812 | |
| MaskPointLearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=22.1, Input Data=2k Points2023.12 | 0.881 | |
| DGCNNLearning Paradigm=Supervised Learning Only, #Params (M)=1.8, Input Data=1k Points2023.12 | 0.862 | |
| PointNet++Learning Paradigm=Supervised Learning Only, #Params (M)=1.5, Input Data=1k Points2023.12 | 0.843 | |
| PointNetLearning Paradigm=Supervised Learning Only, #Params (M)=3.5, Input Data=1k Points2023.12 | 0.792 |