SOTAVerified

3D Point Cloud Classification

Papers

Showing 110 of 202 papers

TitleStatusHype
Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation LearningCode0
Rethinking Gradient-based Adversarial Attacks on Point Cloud Classification0
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point CloudsCode1
DG-MVP: 3D Domain Generalization via Multiple Views of Point Clouds for Classification0
Introducing the Short-Time Fourier Kolmogorov Arnold Network: A Dynamic Graph CNN Approach for Tree Species Classification in 3D Point CloudsCode0
Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional EncodingCode0
AdaCrossNet: Adaptive Dynamic Loss Weighting for Cross-Modal Contrastive Point Cloud LearningCode0
Rethinking Masked Representation Learning for 3D Point Cloud UnderstandingCode0
Point-GN: A Non-Parametric Network Using Gaussian Positional Encoding for Point Cloud ClassificationCode1
Test-Time Adaptation in Point Clouds: Leveraging Sampling Variation with Weight AveragingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PointNetError Rate0.28Unverified
2SimpleViewError Rate0.27Unverified
3RSCNNError Rate0.26Unverified
4DGCNNError Rate0.26Unverified
5PCTError Rate0.26Unverified
6PointNet++Error Rate0.24Unverified
7PointNet++/+PointMixupError Rate0.19Unverified
8PointNet++/+PointCutMix-RError Rate0.19Unverified
9DGCNN+PointCutMix-RError Rate0.17Unverified
10PCT+RSMixError Rate0.17Unverified