SOTAVerified

Point Cloud Classification

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

Papers

Showing 131140 of 265 papers

TitleStatusHype
Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud ClassificationCode0
SGAS: Sequential Greedy Architecture SearchCode0
DualMLP: a two-stream fusion model for 3D point cloud classificationCode0
Geometric Back-projection Network for Point Cloud ClassificationCode0
Adversarial shape perturbations on 3D point cloudsCode0
DuMLP-Pin: A Dual-MLP-dot-product Permutation-invariant Network for Set Feature ExtractionCode0
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on GraphsCode0
AGConv: Adaptive Graph Convolution on 3D Point CloudsCode0
Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding0
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency0
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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