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 161–170 of 265 papers

TitleStatusHype
3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks—0
Text2Model: Text-based Model Induction for Zero-shot Image Classification—0
PointShuffleNet: Learning Non-Euclidean Features with Homotopy Equivalence and Mutual Information—0
A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation—0
Action Keypoint Network for Efficient Video Recognition—0
Adaptive Channel Encoding Transformer for Point Cloud Analysis—0
Adaptive Point Transformer—0
Adversarial Attack by Limited Point Cloud Surface Modifications—0
Adversarial Attacks and Defenses on 3D Point Cloud Classification: A Survey—0
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets—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