SOTAVerified

Point Cloud Classification

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

Papers

Showing 2130 of 265 papers

TitleStatusHype
APSNet: Attention Based Point Cloud SamplingCode1
Exploiting Inductive Bias in Transformer for Point Cloud Classification and SegmentationCode1
3DCTN: 3D Convolution-Transformer Network for Point Cloud ClassificationCode1
Deep Declarative Networks: A New HopeCode1
Collect-and-Distribute Transformer for 3D Point Cloud AnalysisCode1
CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-trainingCode1
A Closer Look at Few-Shot 3D Point Cloud ClassificationCode1
Deep SetsCode1
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation LearningCode1
Differentiable Euler Characteristic Transforms for Shape ClassificationCode1
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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