3D object classification on ScanObjectNN OBJ_ONLY
94.2Overall AccuracyMVNet-L
Evaluation Results
| Method | Links | |
|---|---|---|
| MVNet-LPre-training Dataset=Objaverse, Feature Dimension=7682025.12 | 94.2 | |
| 3D-JEPAPre-training Epochs=300, Training Paradigm=SSRL2024.09 | 93.63 | |
| PointSD2026.06 | 93.6 | |
| ReCon#P (M)=43.6, #F (G)=5.3, Training Paradigm=with Pretrained Cross-Modal Teacher Representation Learning2023.07 | 93.29 | |
| Point-DAE2026.06 | 93.1 | |
| 3D-JEPAPre-training Epochs=150, Training Paradigm=SSRL2024.09 | 92.77 | |
| PRISMcombination=with Point-MAE2026.06 | 92.7 | |
| MVTN2020.11 | 92.3 | |
| PRISM2026.06 | 92.1 | |
| MaskFeat3DBackbone=PointNeXt2025.12 | 92 | |
| VPP w/ vot.#P (M)=22.1, #F (G)=4.8, Training Paradigm=with Self-Supervised Representation Learning, Voting Strategy=Yes2023.07 | 91.91 | |
| ACT#P (M)=22.1, #F (G)=4.8, Training Paradigm=with Pretrained Cross-Modal Teacher Representation Learning2023.07 | 91.91 | |
| ACTPre-training Epochs=300, Training Paradigm=SSRL2024.09 | 91.91 | |
| PointDif2026.06 | 91.9 | |
| IAE (M2AE)#Params(M)=15.3, GFLOPS=3.6, Evaluation Protocol=FULL SSL2025.12 | 91.6 | |
| I2P-MAE#P (M)=12.9, #F (G)=3.6, Training Paradigm=with Pretrained Cross-Modal Teacher Representation Learning2023.07 | 91.57 | |
| VPP w/o vot.#P (M)=22.1, #F (G)=4.8, Training Paradigm=with Self-Supervised Representation Learning, Voting Strategy=No2023.07 | 91.56 | |
| IAE (M2AE)#Params(M)=15.3, GFLOPS=3.6, Evaluation Protocol=FULL SSL, pre-training mesh=w/o mesh2025.12 | 91.2 | |
| PointNeXt2025.12 | 91 | |
| Point2VecPre-training Epochs=300, Training Paradigm=SSRL2024.09 | 90.4 | |
| MVNet-BPre-training Dataset=Objaverse2025.12 | 90.1 | |
| MaskFeat3DBackbone=PointViT2025.12 | 90 | |
| MVNet-BPre-training Dataset=ShapeNet2025.12 | 89.7 | |
| ULIPPre-training Dataset=ShapeNet2025.12 | 89.4 | |
| MaskDiscrPre-training Dataset=ShapeNet2025.12 | 89.3 | |
| MaskSurfelPre-training Dataset=ShapeNet2025.12 | 89.2 | |
| IAE (DGCNN)#Params(M)=1.8, GFLOPS=2.4, Evaluation Protocol=FULL SSL2025.12 | 89 | |
| Point-M2AE#P (M)=14.8, #F (G)=3.6, Training Paradigm=with Self-Supervised Representation Learning2023.07 | 88.81 | |
| Point-M2AEPre-training Epochs=300, Training Paradigm=SSRL2024.09 | 88.81 | |
| Point-M2AE#Params(M)=15.3, GFLOPS=3.6, Evaluation Protocol=FULL SSL2025.12 | 88.8 | |
| Point-M2AE2026.06 | 88.8 | |
| 3D-OAEPre-training Epochs=300, Training Paradigm=SSRL2024.09 | 88.64 | |
| Point-MAE#Params(M)=22.1, GFLOPS=4.8, Evaluation Protocol=FULL SSL2025.12 | 88.3 | |
| PointMAEPre-training Dataset=ShapeNet2025.12 | 88.3 | |
| Point-MAE2026.06 | 88.3 | |
| Point-MAE#P (M)=22.1, #F (G)=4.8, Training Paradigm=with Self-Supervised Representation Learning2023.07 | 88.29 | |
| Point-MAEPre-training Epochs=300, Training Paradigm=SSRL2024.09 | 88.29 | |
| PointMLP2025.12 | 88.2 | |
| PTv3training=from scratch2026.06 | 88.2 | |
| Point-BERT#P (M)=22.1, #F (G)=4.8, Training Paradigm=with Self-Supervised Representation Learning2023.07 | 88.12 | |
| Point-BERTPre-training Epochs=300, Training Paradigm=SSRL2024.09 | 88.12 | |
| Point-BERT#Params(M)=22.1, GFLOPS=4.8, Evaluation Protocol=FULL SSL2025.12 | 88.1 | |
| PointBERTPre-training Dataset=ShapeNet2025.12 | 88.1 | |
| TAMMPre-Training Dataset=Ensembled, Evaluation Protocol=Linear Probing2024.02 | 88 | |
| OcCo#Params(M)=1.8, GFLOPS=2.4, Evaluation Protocol=FULL SSL2025.12 | 87.5 | |
| Point-BERT2026.06 | 87.4 | |
| MaskFeat3DBackbone=MinkowskiNet2025.12 | 87 | |
| DGCNN#P (M)=1.8, #F (G)=2.4, Training Paradigm=Supervised Learning Only2023.07 | 86.2 | |
| DGCNNPre-training Epochs=N/A, Training Paradigm=Supervised Learning Only2024.09 | 86.2 | |
| DGCNN#Params(M)=1.8, GFLOPS=2.4, Evaluation Protocol=FULL SSL2025.12 | 86.2 | |
| DGCNN2025.12 | 86.2 | |
| DGCNN2020.11 | 86.2 | |
| MinkowskiNet2025.12 | 86.1 | |
| PointCNN#P (M)=0.6, Training Paradigm=Supervised Learning Only2023.07 | 85.5 | |
| PointCNN#Params(M)=0.6, Evaluation Protocol=Supervised2025.12 | 85.5 | |
| PointCNN2025.12 | 85.5 | |
| PointCNN2020.11 | 85.5 | |
| OpenShapePre-Training Dataset=Ensembled, Evaluation Protocol=Linear Probing2024.02 | 85.4 | |
| PointNet++#P (M)=1.5, #F (G)=1.7, Training Paradigm=Supervised Learning Only2023.07 | 84.3 | |
| PointNet++Pre-training Epochs=N/A, Training Paradigm=Supervised Learning Only2024.09 | 84.3 | |
| PointNet++#Params(M)=1.5, GFLOPS=1.7, Evaluation Protocol=Supervised2025.12 | 84.3 | |
| PointNet++2025.12 | 84.3 | |
| PointNet ++2020.11 | 84.3 | |
| KPConvEvaluation Protocol=Supervised2025.12 | 84.1 | |
| Transformer#Params(M)=22.1, GFLOPS=4.8, Evaluation Protocol=FULL SSL2025.12 | 84.1 | |
| Transformer#P (M)=22.1, #F (G)=4.8, Training Paradigm=with Self-Supervised Representation Learning2023.07 | 84.06 | |
| TransformerPre-training Epochs=300, Training Paradigm=SSRL2024.09 | 84.06 | |
| TAMMPre-Training Dataset=ShapeNet, Evaluation Protocol=Linear Probing2024.02 | 81.1 | |
| TransformerEvaluation Protocol=from scratch2025.12 | 80.6 | |
| SpiderCNN2020.11 | 79.5 | |
| PointNet#P (M)=3.5, #F (G)=0.5, Training Paradigm=Supervised Learning Only2023.07 | 79.2 | |
| PointNetPre-training Epochs=N/A, Training Paradigm=Supervised Learning Only2024.09 | 79.2 | |
| PointNet#Params(M)=3.5, GFLOPS=0.5, Evaluation Protocol=Supervised2025.12 | 79.2 | |
| PointNet2025.12 | 79.2 | |
| PointNet2020.11 | 79.2 | |
| OpenShapePre-Training Dataset=ShapeNet, Evaluation Protocol=Linear Probing2024.02 | 78.5 | |
| ULIPPre-Training Dataset=ShapeNet, Evaluation Protocol=Linear Probing2024.02 | 75.4 | |
| 3DMFV2020.11 | 73.8 | |
| P3TCross-dataset generalization=true, Source dataset=Objaverse-LVIS2026.04 | 52.8 | |
| Point-PRCCross-dataset generalization=true, Source dataset=Objaverse-LVIS2026.04 | 45.1 | |
| PPTCross-dataset generalization=true, Source dataset=Objaverse-LVIS2026.04 | 39.8 | |
| ULIP-2 (ZS)Zero-shot setting=true, Cross-dataset generalization=true, Source dataset=Objaverse-LVIS2026.04 | 32.2 | |
| ULIP-2Cross-dataset generalization=true, Source dataset=Objaverse-LVIS2026.04 | 23.4 |