SOTAVerified

Point Cloud Classification

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

Papers

Showing 4150 of 265 papers

TitleStatusHype
Visualizing Global Explanations of Point Cloud DNNsCode1
Quasi-Balanced Self-Training on Noise-Aware Synthesis of Object Point Clouds for Closing Domain GapCode1
3DCTN: 3D Convolution-Transformer Network for Point Cloud ClassificationCode1
LPF-Defense: 3D Adversarial Defense based on Frequency AnalysisCode1
Benchmarking and Analyzing Point Cloud Classification under CorruptionsCode1
Learnable Lookup Table for Neural Network QuantizationCode1
Why Discard if You Can Recycle?: A Recycling Max Pooling Module for 3D Point Cloud AnalysisCode1
Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point ModelingCode1
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point CloudsCode1
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation LearningCode1
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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