SOTAVerified

Point Cloud Classification

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–100 of 265 papers

TitleStatusHype
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
ModelNet-O: A Large-Scale Synthetic Dataset for Occlusion-Aware Point Cloud ClassificationCode1
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
Frozen Transformers in Language Models Are Effective Visual Encoder LayersCode2
Differentiable Euler Characteristic Transforms for Shape ClassificationCode1
DualMLP: a two-stream fusion model for 3D point cloud classificationCode0
Edge Aware Learning for 3D Point Cloud—0
Robust Point Cloud Processing through Positional EmbeddingCode1
Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation—0
Robustifying Point Cloud Networks by RefocusingCode0
Risk-optimized Outlier Removal for Robust 3D Point Cloud ClassificationCode1
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
Collect-and-Distribute Transformer for 3D Point Cloud AnalysisCode1
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
SUG: Single-dataset Unified Generalization for 3D Point Cloud ClassificationCode1
Exploiting Inductive Bias in Transformer for Point Cloud Classification and SegmentationCode1
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
A Closer Look at Few-Shot 3D Point Cloud ClassificationCode1
What Makes for Effective Few-shot Point Cloud Classification?Code1
Local region-learning modules for point cloud classification—0
EPiC: Ensemble of Partial Point Clouds for Robust ClassificationCode0
Interpreting Hidden Semantics in the Intermediate Layers of 3D Point Cloud Classification Neural Network—0
Point Cloud Classification Using Content-based Transformer via Clustering in Feature SpaceCode1
PointCert: Point Cloud Classification with Deterministic Certified Robustness Guarantees—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
PointWavelet: Learning in Spectral Domain for 3D Point Cloud Analysis—0
Dynamic Local Feature Aggregation for Learning on Point CloudsCode1
Improved Training for 3D Point Cloud ClassificationCode0
Computation and Data Efficient Backdoor Attacks—0
Show:102550
← PrevPage 2 of 6Next →
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