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 51–75 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
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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