SOTAVerified

Point Cloud Classification

Point Cloud Classification is a task involving the classification of unordered 3D point sets (point clouds).

Papers

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Showing 101–150 of 265 papers

TitleStatusHype
PMT-MAE: Dual-Branch Self-Supervised Learning with Distillation for Efficient Point Cloud Classification—0
SA-MLP: A Low-Power Multiplication-Free Deep Network for 3D Point Cloud Classification in Resource-Constrained EnvironmentsCode0
Efficient Point Cloud Classification via Offline Distillation Framework and Negative-Weight Self-Distillation Technique—0
PointDGMamba: Domain Generalization of Point Cloud Classification via Generalized State Space ModelCode0
Enhancing Sampling Protocol for Point Cloud Classification Against Corruptions—0
Temporal Reversed Training for Spiking Neural Networks with Generalized Spatio-Temporal Representation—0
CLIP-based Point Cloud Classification via Point Cloud to Image Translation—0
Rethinking Attention Module Design for Point Cloud Analysis—0
Boosting Cross-Domain Point Classification via Distilling Relational Priors from 2D TransformersCode0
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
Leveraging PointNet and PointNet++ for Lyft Point Cloud Classification Challenge—0
CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction—0
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets—0
Meta Episodic learning with Dynamic Task Sampling for CLIP-based Point Cloud Classification—0
Image and Point-cloud Classification for Jet Analysis in High-Energy Physics: A survey—0
FBPT: A Fully Binary Point Transformer—0
Classifying Objects in 3D Point Clouds Using Recurrent Neural Network: A GRU LSTM Hybrid ApproachCode0
A Benchmark Grocery Dataset of Realworld Point Clouds From Single View—0
Classifying point clouds at the facade-level using geometric features and deep learning networksCode0
Adaptive Point Transformer—0
3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar dataCode0
Exploiting GPT-4 Vision for Zero-shot Point Cloud Understanding—0
Point Cloud Classification via Deep Set Linearized Optimal Transport—0
CausalPC: Improving the Robustness of Point Cloud Classification by Causal Effect Identification—0
PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis—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
Learning-Based Biharmonic Augmentation for Point Cloud Classification—0
Deep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook—0
Deep Learning-based Compressed Domain Multimedia for Man and Machine: A Taxonomy and Application to Point Cloud Classification—0
DualMLP: a two-stream fusion model for 3D point cloud classificationCode0
Edge Aware Learning for 3D Point Cloud—0
Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation—0
Robustifying Point Cloud Networks by RefocusingCode0
Learning Adaptive Neighborhoods for Graph Neural Networks—0
3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks—0
Adversarial Attacks and Defenses on 3D Point Cloud Classification: A Survey—0
Feature Adversarial Distillation for Point Cloud Classification—0
Semantic-aware Transmission for Robust Point Cloud Classification—0
Equivariant vs. Invariant Layers: A Comparison of Backbone and Pooling for Point Cloud ClassificationCode0
Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits—0
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs—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
Local region-learning modules for point cloud classification—0
EPiC: Ensemble of Partial Point Clouds for Robust ClassificationCode0
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All datasetsPointCloud-CISPRS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PointNetmean Corruption Error (mCE)1.42—Unverified
2WOLFMix (PointNet)mean Corruption Error (mCE)1.18—Unverified
3PointNetmean Corruption Error (mCE)1.18—Unverified
4RSCNNmean Corruption Error (mCE)1.13—Unverified
5PAConvmean Corruption Error (mCE)1.1—Unverified
6SimpleViewmean Corruption Error (mCE)1.05—Unverified
7OcCo-DGCNNmean Corruption Error (mCE)1.05—Unverified
8PointMixUp (PointNet++)mean Corruption Error (mCE)1.03—Unverified
9DGCNNmean Corruption Error (mCE)1—Unverified
10OcCo-DGCNNmean Corruption Error (mCE)0.98—Unverified
#ModelMetricClaimedVerifiedStatus
1OursAverage F182.8—Unverified