SOTAVerified

Point Cloud Classification

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

Papers

Showing 6170 of 265 papers

TitleStatusHype
PointCutMix: Regularization Strategy for Point Cloud ClassificationCode1
Revisiting Point Cloud Classification with a Simple and Effective BaselineCode1
Geometry-Aware Self-Training for Unsupervised Domain Adaptation on Object Point CloudsCode1
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point CloudCode1
PCT: Point cloud transformerCode1
RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud ClassifiersCode1
Unsupervised Point Cloud Pre-Training via Occlusion CompletionCode1
PointMixup: Augmentation for Point CloudsCode1
Point Set Voting for Partial Point Cloud AnalysisCode1
Parameter-Efficient Person Re-identification in the 3D SpaceCode1
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Benchmark Results

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