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ResearchFormerly WizWand

3D Classification on ScanObjectNN OBJ-BG official

96.4AccuracyP3T
72.37678.61384.8591.087Sep 25, 2023Feb 27, 2024Aug 1, 2024Jan 4, 2025Jun 9, 2025Nov 12, 2025Apr 17, 2026
Updated 6mo ago

Evaluation results

MethodLinks
P3T#LP (M)=2.0, Training Protocol=Self-Supervised Pre-training + Parameter-efficient fine-tuning, PPT Setting=true2026.0496.4
Point-RAEEvaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.0995.53
PPT#LP (M)=1.8, Training Protocol=Self-Supervised Pre-training + Parameter-efficient fine-tuning, PPT Setting=true2026.0495.4
P3T#LP (M)=2.0, Training Protocol=Self-Supervised Pre-training + Parameter-efficient fine-tuning, PPT Setting=false2026.0495.2
RECON#LP (M)=43.6, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0494.2
I2P-MAEYear=2023, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.0994.15
PPT#LP (M)=1.8, Training Protocol=Self-Supervised Pre-training + Parameter-efficient fine-tuning, PPT Setting=false2026.0493.7
ACT#LP (M)=22.1, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0493.3
ACTYear=2023, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.0993.29
MVTNYear=2021, Evaluation Protocol=Supervised Learning Only2023.0992.6
MVTN#LP (M)=11.2, Training Protocol=Supervised Learning, PPT Setting=false2026.0492.6
ULIP-2#LP (M)=22.1, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0491.9
ULIP#LP (M)=22.1, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0491.7
PointGPT#LP (M)=29.2, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0491.6
Point-M2AEYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.0991.22
Point-M2AE#LP (M)=15.3, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0491.2
Point-PRC#LP (M)=0.02, Training Protocol=Self-Supervised Pre-training + Parameter-efficient fine-tuning, PPT Setting=true2026.0490.2
Point-MAEYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.0990.02
Point-MAE#LP (M)=22.1, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0490
MaskPoint#LP (M)=22.1, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0489.7
MaskPointYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.0989.3
Point-PRC#LP (M)=0.02, Training Protocol=Self-Supervised Pre-training + Parameter-efficient fine-tuning, PPT Setting=false2026.0489
Point-BERTYear=2022, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.0987.43
Point-BERT#LP (M)=22.1, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0487.4
DAPT#LP (M)=0.8, Training Protocol=Self-Supervised Pre-training + Parameter-efficient fine-tuning, PPT Setting=false2026.0487.1
PointCNNYear=2018, Evaluation Protocol=Supervised Learning Only2023.0986.1
PointCNN#LP (M)=0.6, Training Protocol=Supervised Learning, PPT Setting=false2026.0486.1
OcCo#LP (M)=22.1, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0484.9
IDPT#LP (M)=1.3, Training Protocol=Self-Supervised Pre-training + Parameter-efficient fine-tuning, PPT Setting=false2026.0484.9
DGCNNYear=2019, Evaluation Protocol=Supervised Learning Only2023.0982.8
DGCNN#LP (M)=1.8, Training Protocol=Supervised Learning, PPT Setting=false2026.0482.8
PointNet++Year=2017, Evaluation Protocol=Supervised Learning Only2023.0982.3
PointNet++#LP (M)=1.5, Training Protocol=Supervised Learning, PPT Setting=false2026.0482.3
CrossPoint#LP (M)=27.7, Training Protocol=Self-Supervised Pre-training + Full fine-tuning, PPT Setting=false2026.0481.7
TransformerYear=2017, Evaluation Protocol=with Self-Supervised Representation Learning (FULL)2023.0979.86
PointNetYear=2016, Evaluation Protocol=Supervised Learning Only2023.0973.3
PointNet#LP (M)=3.5, Training Protocol=Supervised Learning, PPT Setting=false2026.0473.3