SOTAVerified

Point Cloud Classification

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

Papers

Showing 171180 of 265 papers

TitleStatusHype
3DGTN: 3D Dual-Attention GLocal Transformer Network for Point Cloud Classification and Segmentation0
SimpleView++: Neighborhood Views for Point Cloud ClassificationCode0
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification0
Boosting Point-BERT by Multi-choice TokensCode0
Explaining Deep Neural Networks for Point Clouds using Gradient-based Visualisations0
Enhancing Local Feature Learning Using Diffusion for 3D Point Cloud Understanding0
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces0
AGConv: Adaptive Graph Convolution on 3D Point CloudsCode0
Transformers in 3D Point Clouds: A Survey0
Topologically Persistent Features-based Object Recognition in Cluttered Indoor Environments0
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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