SOTAVerified

Point Cloud Classification

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

Papers

Showing 231240 of 265 papers

TitleStatusHype
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on GraphsCode0
Semantic3D.net: A new Large-scale Point Cloud Classification BenchmarkCode0
Grid-GCN for Fast and Scalable Point Cloud LearningCode0
DualMLP: a two-stream fusion model for 3D point cloud classificationCode0
BeyondRPC: A Contrastive and Augmentation-Driven Framework for Robust Point Cloud UnderstandingCode0
SGAS: Sequential Greedy Architecture SearchCode0
Adaptive Graph Convolution for Point Cloud AnalysisCode0
A Graph-CNN for 3D Point Cloud ClassificationCode0
AdvectiveNet: An Eulerian-Lagrangian Fluidic reservoir for Point Cloud ProcessingCode0
URSA: A Neural Network for Unordered Point Clouds Using ConstellationsCode0
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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