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Few-shot Classification on ModelNet40 (5-way, 20-shot)

99.4AccuracyCSCon
38.45654.27870.185.922Apr 14, 2023Oct 17, 2023Apr 20, 2024Oct 23, 2024Apr 27, 2025Oct 30, 2025May 5, 2026

Evaluation results

MethodLinks
CSConProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1299.4
PCP-MAEProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1299.1
PCP-MAEEvaluation Protocol=MLP-32025.1299.1
CSConEvaluation Protocol=MLP-32025.1299.1
PointLAMAProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1299
PointGPT-SEvaluation Protocol=Full Fine-tuning2026.0599
PointMambaEvaluation Protocol=Parameter-Efficient Fine-Tuning2026.0599
PointMamba + MantisEvaluation Protocol=Parameter-Efficient Fine-Tuning2026.0599
ZigzagPointMambaEvaluation Protocol=Parameter-Efficient Fine-Tuning2026.0599
ZigzagPointMamba + MantisEvaluation Protocol=Parameter-Efficient Fine-Tuning2026.0599
RECON (Full-FT)Publication=ICML'23, Fine-tuning Protocol=Full Fine-Tuning2025.0498.9
Point-PQAEProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1298.9
DAP-MAEProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1298.9
ReConProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=cross-modal information and teacher models2025.1298.9
Point-FEMAEEvaluation Protocol=MLP-LINEAR2025.1298.9
Point-FEMAEEvaluation Protocol=MLP-32025.1298.9
ReConEvaluation Protocol=Full Fine-tuning2026.0598.9
Mamba3D + MantisEvaluation Protocol=Parameter-Efficient Fine-Tuning2026.0598.9
RECON+ PointLoRAPublication=Ours, Fine-tuning Protocol=Efficient Fine-Tuning2025.0498.8
CSConEvaluation Protocol=MLP-LINEAR2025.1298.8
Point-RAEvoting=false2023.0998.7
RECON+ PPTPublication=arXiv'24, Fine-tuning Protocol=Efficient Fine-Tuning2025.0498.7
PointGPTProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1298.6
Point-FEMAEProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1298.6
ReConEvaluation Protocol=MLP-32025.1298.5
Point-M2AELearning Protocol=Full Fine-tuning2023.0498.3
Point-M2AEvoting=false2023.0998.3
I2P-MAEvoting=false2023.0998.3
Point-M2AEPublication=NeurIPS'22, Fine-tuning Protocol=Full Fine-Tuning2025.0498.3
RECON+ IDPTPublication=ICCV'23, Fine-tuning Protocol=Efficient Fine-Tuning2025.0498.3
Point-M2AEProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1298.3
I2P-MAEProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=cross-modal information and teacher models2025.1298.3
ACT w/ IDPTLearning Protocol=IDPT2023.0498.2
MAMBA3D+P-MLearning Mode=Self-supervised Pre-training, Pre-training Strategy=Point-MAE, Voting=false2024.0498.2
ReConEvaluation Protocol=MLP-LINEAR2025.1298.2
Point-PQAEEvaluation Protocol=MLP-32025.1298.2
Mamba3DEvaluation Protocol=Parameter-Efficient Fine-Tuning2026.0598.2
ACTLearning Protocol=Full Fine-tuning2023.0498
ACTvoting=false2023.0998
ACTPublication=ICLR'23, Fine-tuning Protocol=Full Fine-Tuning2025.0498
Point-CMAEProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1298
ACTProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=cross-modal information and teacher models2025.1298
ACTEvaluation Protocol=Full Fine-tuning2026.0598
Point-MAE w/ IDPTLearning Protocol=IDPT2023.0497.9
MAMBA3D+P-BLearning Mode=Self-supervised Pre-training, Pre-training Strategy=Point-BERT, Voting=false2024.0497.9
Joint-MAEProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=cross-modal information and teacher models2025.1297.9
Point-MAELearning Protocol=Full Fine-tuning2023.0497.8
Point-MAEvoting=false2023.0997.8
Point-MAELearning Mode=Self-supervised Pre-training, Voting=false2024.0497.8
Point-MAEPublication=ECCV'22, Fine-tuning Protocol=Full Fine-Tuning2025.0497.8
Point-MAEProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1297.8
TAPProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=cross-modal information and teacher models2025.1297.8
PCP-MAEEvaluation Protocol=MLP-LINEAR2025.1297.8
Point-MAEEvaluation Protocol=Full Fine-tuning2026.0597.8
RECON+ DAPTPublication=CVPR'24, Fine-tuning Protocol=Efficient Fine-Tuning2025.0497.7
ACTEvaluation Protocol=MLP-32025.1297.7
Point-CMAEEvaluation Protocol=MLP-32025.1297.5
EPCLLearning Protocol=Full Fine-tuning2023.0497.3
PointMambaLearning Mode=Self-supervised Pre-training, Voting=false2024.0497.3
MaskPointLearning Protocol=Full Fine-tuning2023.0497.2
Point-BERT w/ IDPTLearning Protocol=IDPT2023.0497.2
MaskPointvoting=false2023.0997.2
MaskPointLearning Mode=Self-supervised Pre-training, Voting=false2024.0497.2
MaskPointPublication=ECCV'22, Fine-tuning Protocol=Full Fine-Tuning2025.0497.2
MaskPointProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1297.2
MaskPointEvaluation Protocol=Full Fine-tuning2026.0597.2
MAMBA3DLearning Mode=Supervised Learning, Voting=false2024.0496.9
Point-PQAEEvaluation Protocol=MLP-LINEAR2025.1296.8
Point-MAEEvaluation Protocol=MLP-32025.1296.7
Point-BERTLearning Protocol=Full Fine-tuning2023.0496.3
Point-BERTvoting=false2023.0996.3
Point-BERTLearning Mode=Self-supervised Pre-training, Voting=false2024.0496.3
Point-BERTPublication=CVPR'22, Fine-tuning Protocol=Full Fine-Tuning2025.0496.3
Point-BERTProtocol=FULL, Training Paradigm=Self-Supervised Representation Learning, Input Modality=single-modal information2025.1296.3
Point-BERTEvaluation Protocol=Full Fine-tuning2026.0596.3
Transformer-OcCoLearning Protocol=Full Fine-tuning2023.0495.9
OcCoLearning Mode=Self-supervised Pre-training, Voting=false2024.0495.9
OcCoPublication=ICCV'21, Fine-tuning Protocol=Full Fine-Tuning2025.0495.9
SLNet-MMethod Category=Parametric2026.0395
Point-CMAEEvaluation Protocol=MLP-LINEAR2025.1294.1
Transformervoting=false2023.0993.3
TransformerLearning Mode=Supervised Learning, Voting=false2024.0493.3
NPNetMethod Category=Non-Parametric2026.0393.2
ACTEvaluation Protocol=MLP-LINEAR2025.1293.1
DGCNN-OcCoLearning Protocol=Full Fine-tuning2023.0492.5
DGCNN+OcCovoting=false2023.0992.5
DGCNN+OcCoLearning Mode=Self-supervised Pre-training, Pre-training Strategy=OcCo, Voting=false2024.0492.5
OcCoProtocol=FULL, Training Paradigm=Supervised Learning Only2025.1292.5
Point-MAEEvaluation Protocol=MLP-LINEAR2025.1291.7
Point-NNMethod Category=Non-Parametric2026.0390.9
Point-GNMethod Category=Non-Parametric2026.0390.9
SLNet-SMethod Category=Parametric2026.0389
PointCNNMethod Category=Parametric2026.0368.6
3D-GANMethod Category=Parametric2026.0365.8
PointNetProtocol=FULL, Training Paradigm=Supervised Learning Only2025.1257.8
PointNetMethod Category=Parametric2026.0357.8
PointNet++Method Category=Parametric2026.0342.4
DGCNNvoting=false2023.0940.8
DGCNNLearning Mode=Supervised Learning, Voting=false2024.0440.8
DGCNNProtocol=FULL, Training Paradigm=Supervised Learning Only2025.1240.8