SOTAVerified

Point Cloud Classification

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

Papers

Showing 121130 of 265 papers

TitleStatusHype
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on GraphsCode0
DuMLP-Pin: A Dual-MLP-dot-product Permutation-invariant Network for Set Feature ExtractionCode0
BeyondRPC: A Contrastive and Augmentation-Driven Framework for Robust Point Cloud UnderstandingCode0
Improved Training for 3D Point Cloud ClassificationCode0
DualMLP: a two-stream fusion model for 3D point cloud classificationCode0
Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud ClassificationCode0
Adaptive Graph Convolution for Point Cloud AnalysisCode0
On Automatic Data Augmentation for 3D Point Cloud ClassificationCode0
PatchAugment: Local Neighborhood Augmentation in Point Cloud ClassificationCode0
ACNe: Attentive Context Normalization for Robust Permutation-Equivariant LearningCode0
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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