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 71–80 of 265 papers

TitleStatusHype
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
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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