SOTAVerified

3D Point Cloud Classification

Papers

Showing 125 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
Beyond local patches: Preserving global–local interactions by enhancing self-attention via 3D point cloud tokenization0
Low-Density 3D Point Cloud Classification0
PointNet with KAN versus PointNet with MLP for 3D Classification and Segmentation of Point SetsCode1
Robust 3D Point Clouds Classification based on Declarative DefendersCode1
Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud LearningCode3
3D-JEPA: A Joint Embedding Predictive Architecture for 3D Self-Supervised Representation Learning0
SA-MLP: A Low-Power Multiplication-Free Deep Network for 3D Point Cloud Classification in Resource-Constrained EnvironmentsCode0
Positional Prompt Tuning for Efficient 3D Representation LearningCode1
Temporal Reversed Training for Spiking Neural Networks with Generalized Spatio-Temporal Representation0
PCP-MAE: Learning to Predict Centers for Point Masked AutoencodersCode2
RISurConv: Rotation Invariant Surface Attention-Augmented Convolutions for 3D Point Cloud Classification and SegmentationCode1
GPSFormer: A Global Perception and Local Structure Fitting-based Transformer for Point Cloud UnderstandingCode1
Transferable 3D Adversarial Shape Completion using Diffusion ModelsCode0
Eidos: Efficient, Imperceptible Adversarial 3D Point Clouds0
KPConvX: Modernizing Kernel Point Convolution with Kernel AttentionCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PointGSTOverall Accuracy95.3Unverified
2Mamba3D + Point-MAEOverall Accuracy95.1Unverified
3ReCon++Overall Accuracy95Unverified
4PointGPTOverall Accuracy94.9Unverified
5point2vecOverall Accuracy94.8Unverified
6AsymDSD-B* (no voting)Overall Accuracy94.7Unverified
7ULIP + PointMLPOverall Accuracy94.7Unverified
8ReConOverall Accuracy94.7Unverified
9RepSurf-UOverall Accuracy94.7Unverified
10PointMLP+HyCoReOverall Accuracy94.5Unverified
#ModelMetricClaimedVerifiedStatus
1OmniVec2Overall Accuracy97.2Unverified
2PointGSTOverall Accuracy96.18Unverified
3OmniVecOverall Accuracy96.1Unverified
4GPSFormerOverall Accuracy95.4Unverified
5ReCon++Overall Accuracy95.25Unverified
6AsymDSD-B* (no voting)Overall Accuracy93.72Unverified
7PointGPTOverall Accuracy93.4Unverified
8GPSFormer-eliteOverall Accuracy93.3Unverified
9Mamba3DOverall Accuracy92.64Unverified
10Mamba3D (no voting)Overall Accuracy91.81Unverified
#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