SOTAVerified

Point Cloud Classification

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 265 papers

TitleStatusHype
Relation-Shape Convolutional Neural Network for Point Cloud AnalysisCode0
Grid-GCN for Fast and Scalable Point Cloud LearningCode0
Adaptive Graph Convolution for Point Cloud AnalysisCode0
Transferable 3D Adversarial Shape Completion using Diffusion ModelsCode0
AdvectiveNet: An Eulerian-Lagrangian Fluidic reservoir for Point Cloud ProcessingCode0
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 Understanding—0
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency—0
OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization—0
Self-Distillation for Unsupervised 3D Domain Adaptation—0
Semantic-aware Transmission for Robust Point Cloud Classification—0
PMT-MAE: Dual-Branch Self-Supervised Learning with Distillation for Efficient Point Cloud Classification—0
Shape-Oriented Convolution Neural Network for Point Cloud Analysis—0
PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples—0
PointCert: Point Cloud Classification with Deterministic Certified Robustness Guarantees—0
Transformers in Vision: A Survey—0
Point Cloud Classification via Deep Set Linearized Optimal Transport—0
Sparse Convolutions on Continuous Domains for Point Cloud and Event Stream Networks—0
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All datasetsPointCloud-CISPRS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PointNetmean Corruption Error (mCE)1.42—Unverified
2WOLFMix (PointNet)mean Corruption Error (mCE)1.18—Unverified
3PointNetmean Corruption Error (mCE)1.18—Unverified
4RSCNNmean Corruption Error (mCE)1.13—Unverified
5PAConvmean Corruption Error (mCE)1.1—Unverified
6SimpleViewmean Corruption Error (mCE)1.05—Unverified
7OcCo-DGCNNmean Corruption Error (mCE)1.05—Unverified
8PointMixUp (PointNet++)mean Corruption Error (mCE)1.03—Unverified
9DGCNNmean Corruption Error (mCE)1—Unverified
10OcCo-DGCNNmean Corruption Error (mCE)0.98—Unverified
#ModelMetricClaimedVerifiedStatus
1OursAverage F182.8—Unverified