SOTAVerified

3D Point Cloud Classification

Papers

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Showing 101–150 of 202 papers

TitleStatusHype
Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World DataCode1
KPConv: Flexible and Deformable Convolution for Point CloudsCode1
Learning to SampleCode1
Dynamic Graph CNN for Learning on Point CloudsCode1
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric SpaceCode1
3D ShapeNets: A Deep Representation for Volumetric ShapesCode1
Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation LearningCode0
Rethinking Gradient-based Adversarial Attacks on Point Cloud Classification—0
DG-MVP: 3D Domain Generalization via Multiple Views of Point Clouds for Classification—0
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
Beyond local patches: Preserving global–local interactions by enhancing self-attention via 3D point cloud tokenization—0
Low-Density 3D Point Cloud Classification—0
3D-JEPA: A Joint Embedding Predictive Architecture for 3D Self-Supervised Representation Learning—0
SA-MLP: A Low-Power Multiplication-Free Deep Network for 3D Point Cloud Classification in Resource-Constrained EnvironmentsCode0
Temporal Reversed Training for Spiking Neural Networks with Generalized Spatio-Temporal Representation—0
Transferable 3D Adversarial Shape Completion using Diffusion ModelsCode0
Eidos: Efficient, Imperceptible Adversarial 3D Point Clouds—0
A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation—0
CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction—0
A Benchmark Grocery Dataset of Realworld Point Clouds From Single View—0
OmniVec2 - A Novel Transformer based Network for Large Scale Multimodal and Multitask Learning—0
PointMoment:Mixed-Moment-based Self-Supervised Representation Learning for 3D Point Clouds—0
Test-Time Augmentation for 3D Point Cloud Classification and Segmentation—0
OmniVec: Learning robust representations with cross modal sharing—0
Deep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook—0
DualMLP: a two-stream fusion model for 3D point cloud classificationCode0
Adversarial Attacks and Defenses on 3D Point Cloud Classification: A Survey—0
Point-LGMask: Local and Global Contexts Embedding for Point Cloud Pre-training with Multi-Ratio MaskingCode0
CrossMoCo: Multi-modal Momentum Contrastive Learning for Point CloudCode0
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits—0
GTNet: Graph Transformer Network for 3D Point Cloud Classification and Semantic Segmentation—0
Connecting Multi-modal Contrastive Representations—0
Multi-view Vision-Prompt Fusion Network: Can 2D Pre-trained Model Boost 3D Point Cloud Data-scarce Learning?—0
Multi-scale Geometry-aware Transformer for 3D Point Cloud Classification—0
Interpreting Hidden Semantics in the Intermediate Layers of 3D Point Cloud Classification Neural Network—0
CLR-GAM: Contrastive Point Cloud Learning with Guided Augmentation and Feature Mapping—0
S3I-PointHop: SO(3)-Invariant PointHop for 3D Point Cloud Classification—0
Computation and Data Efficient Backdoor Attacks—0
CAP: Robust Point Cloud Classification via Semantic and Structural Modeling—0
FFF: Fragment-Guided Flexible Fitting for Building Complete Protein Structures—0
Improved Training for 3D Point Cloud ClassificationCode0
Text2Model: Text-based Model Induction for Zero-shot Image Classification—0
LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in TransformersCode0
Understanding Key Point Cloud Features for Development Three-dimensional Adversarial Attacks—0
Automated Mobile Attention KPConv Networks via a Wide and Deep Predictor—0
A Simple Strategy to Provable Invariance via Orbit Mapping—0
SimpleView++: Neighborhood Views for Point Cloud ClassificationCode0
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All datasetsModelNet40ScanObjectNNModelNet40-CIntrASydney Urban Objects

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PointGSTOverall Accuracy95.3—Unverified
2Mamba3D + Point-MAEOverall Accuracy95.1—Unverified
3ReCon++Overall Accuracy95—Unverified
4PointGPTOverall Accuracy94.9—Unverified
5point2vecOverall Accuracy94.8—Unverified
6RepSurf-UOverall Accuracy94.7—Unverified
7ReConOverall Accuracy94.7—Unverified
8ULIP + PointMLPOverall Accuracy94.7—Unverified
9AsymDSD-B* (no voting)Overall Accuracy94.7—Unverified
10PointMLP+HyCoReOverall Accuracy94.5—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniVec2Overall Accuracy97.2—Unverified
2PointGSTOverall Accuracy96.18—Unverified
3OmniVecOverall Accuracy96.1—Unverified
4GPSFormerOverall Accuracy95.4—Unverified
5ReCon++Overall Accuracy95.25—Unverified
6AsymDSD-B* (no voting)Overall Accuracy93.72—Unverified
7PointGPTOverall Accuracy93.4—Unverified
8GPSFormer-eliteOverall Accuracy93.3—Unverified
9Mamba3DOverall Accuracy92.64—Unverified
10Mamba3D (no voting)Overall Accuracy91.81—Unverified
#ModelMetricClaimedVerifiedStatus
1PointNetError Rate0.28—Unverified
2SimpleViewError Rate0.27—Unverified
3RSCNNError Rate0.26—Unverified
4DGCNNError Rate0.26—Unverified
5PCTError Rate0.26—Unverified
6PointNet++Error Rate0.24—Unverified
7PointNet++/+PointMixupError Rate0.19—Unverified
8PointNet++/+PointCutMix-RError Rate0.19—Unverified
9PCT+RSMixError Rate0.17—Unverified
10DGCNN+PointCutMix-RError Rate0.17—Unverified