Point Cloud Classification on ScanObjectNN OBJ_BG
95.18Overall AccuracyPoint-FEMAE
Evaluation Results
| Method | Links | |
|---|---|---|
| Point-FEMAELearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=27.4, Input Data=2k Points2023.12 | 95.18 | |
| ReconLearning Paradigm=Cross-Modal Self-Supervised Learning, #Params (M)=44.3, Input Data=2k Points2023.12 | 95.18 | |
| Point-MAE w/ LCMPretrain=MPM, #Params(M)=2.7, FLOPs(G)=1.32024.05 | 94.51 | |
| I2P-MAELearning Paradigm=Cross-Modal Self-Supervised Learning, #Params (M)=15.3, Input Data=2k Points2023.12 | 94.15 | |
| ACT w/ LCMPretrain=MPM, #Params(M)=3.1, FLOPs(G)=2.82024.05 | 94.13 | |
| Point-M2AE w/ LCMPretrain=MPM, #Params(M)=2.5, FLOPs(G)=6.72024.05 | 93.83 | |
| PointGPT-BPretrain=GPT, #Params(M)=120.5, FLOPs(G)=36.2, Evaluation Setting=Original Paper2024.05 | 93.6 | |
| Point-BERT w/ LCMPretrain=MPM, #Params(M)=3.1, FLOPs(G)=2.52024.05 | 93.55 | |
| MaskPoint w/ LCMPretrain=MPM, #Params(M)=3.1, FLOPs(G)=2.52024.05 | 93.31 | |
| ACTLearning Paradigm=Cross-Modal Self-Supervised Learning, #Params (M)=22.1, Input Data=2k Points2023.12 | 93.29 | |
| ACTPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Original Paper2024.05 | 93.29 | |
| PointMambaPretrain=MPM, #Params(M)=12.3, Evaluation Setting=Original Paper2024.05 | 93.29 | |
| Point-M2AEPretrain=MPM, #Params(M)=12.9, FLOPs(G)=7.9, Evaluation Setting=Reproduced downstream setting2024.05 | 93.12 | |
| LCMPretrain=X, #Params(M)=2.7, FLOPs(G)=1.32024.05 | 92.77 | |
| Point-MAEPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Reproduced downstream setting2024.05 | 92.67 | |
| MVTN2020.11 | 92.6 | |
| Point-BERTPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.5, Evaluation Setting=Reproduced downstream setting2024.05 | 92.48 | |
| MaskPointPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.5, Evaluation Setting=Reproduced downstream setting2024.05 | 92.17 | |
| ACTPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Reproduced downstream setting2024.05 | 92.08 | |
| TransformerPretrain=X, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Reproduced downstream setting2024.05 | 91.95 | |
| baselinec=642025.11 | 91.84 | |
| MaskFeat3DBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 91.7 | |
| Point-M2AELearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=15.3, Input Data=2k Points2023.12 | 91.22 | |
| Point-M2AE2023.06 | 91.22 | |
| Point-MAE w/ IDPTPretrain=MPM, #Params(M)=23.3, FLOPs(G)=7.1, Evaluation Setting=Original Paper2024.05 | 91.22 | |
| Point-M2AEPretrain=MPM, #Params(M)=12.9, FLOPs(G)=7.9, Evaluation Setting=Original Paper2024.05 | 91.22 | |
| MaskSurfelBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 91.2 | |
| Joint-MAELearning Paradigm=Cross-Modal Self-Supervised Learning, Input Data=2k Points2023.12 | 90.94 | |
| ExpPoint-MAEunfreeze epoch=2002023.06 | 90.88 | |
| Point-MAE w/ DAPTPretrain=MPM, #Params(M)=22.7, FLOPs(G)=5.0, Evaluation Setting=Original Paper2024.05 | 90.88 | |
| TAP (Ours)Backbone=Standard Transformer, Pre-training=Generative2023.07 | 90.36 | |
| ExpPoint-MAEextra domain adaptation pretraining=true2023.06 | 90.36 | |
| Point-MAEBackbone=Standard Transformer, Pre-training=Generative2023.07 | 90.02 | |
| Point-MAELearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=22.1, Input Data=2k Points2023.12 | 90.02 | |
| Point-MAE2023.06 | 90.02 | |
| Point-MAEPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Original Paper2024.05 | 90.02 | |
| PointMAEBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 90 | |
| MaskDiscrBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 89.7 | |
| MaskPointBackbone=Standard Transformer, Pre-training=Generative2023.07 | 89.3 | |
| MaskPointLearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=22.1, Input Data=2k Points2023.12 | 89.3 | |
| MaskPoint2023.06 | 89.3 | |
| MaskPointPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.5, Evaluation Setting=Original Paper2024.05 | 89.3 | |
| Inter-MAEPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Original Paper2024.05 | 88.7 | |
| PointMambaPretrain=X, #Params(M)=12.3, Evaluation Setting=Original Paper2024.05 | 88.3 | |
| ExpPoint-MAEunfreeze epoch=2502023.06 | 87.44 | |
| Point-BERTBackbone=Standard Transformer, Pre-training=Generative2023.07 | 87.43 | |
| Point-BERTLearning Paradigm=Single-Modal Self-Supervised Learning, #Params (M)=22.1, Input Data=1k Points2023.12 | 87.43 | |
| Point-BERT2023.06 | 87.43 | |
| Point-BERTPretrain=MPM, #Params(M)=22.1, FLOPs(G)=4.5, Evaluation Setting=Original Paper2024.05 | 87.43 | |
| PointBERTBackbone=PointViT, Evaluation Protocol=fine-tuning2025.12 | 87.4 | |
| TransformerPretrain=X, #Params(M)=22.1, FLOPs(G)=4.8, Evaluation Setting=Original Paper2024.05 | 86.75 | |
| Foundrys=16, Frozen student=false2025.11 | 86.23 | |
| PointCNN2020.11 | 86.1 | |
| OcCoBackbone=Standard Transformer, Pre-training=Generative2023.07 | 84.85 | |
| DGCNNLearning Paradigm=Supervised Learning Only, #Params (M)=1.8, Input Data=1k Points2023.12 | 82.8 | |
| DGCNN2020.11 | 82.8 | |
| PointNet++Learning Paradigm=Supervised Learning Only, #Params (M)=1.5, Input Data=1k Points2023.12 | 82.3 | |
| PointNet++Pretrain=X, #Params(M)=1.5, FLOPs(G)=1.7, Evaluation Setting=Original Paper2024.05 | 82.3 | |
| PointNet ++2020.11 | 82.3 | |
| PointViTBackbone=PointViT, Evaluation Protocol=from scratch2025.12 | 79.9 | |
| w/o pre-trainingBackbone=Standard Transformer, Pre-training=None2023.07 | 79.86 | |
| SpiderCNN2020.11 | 77.1 | |
| PointNetLearning Paradigm=Supervised Learning Only, #Params (M)=3.5, Input Data=1k Points2023.12 | 73.3 | |
| PointNetPretrain=X, #Params(M)=3.5, FLOPs(G)=0.5, Evaluation Setting=Original Paper2024.05 | 73.3 | |
| PointNet2020.11 | 73.3 | |
| 3DMFV2020.11 | 68.2 |