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 151–175 of 265 papers

TitleStatusHype
PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis—0
PointGuard: Provably Robust 3D Point Cloud Classification—0
SRINet: Learning Strictly Rotation-Invariant Representations for Point Cloud Classification and Segmentation—0
STREAM: A Universal State-Space Model for Sparse Geometric Data—0
PointMoment:Mixed-Moment-based Self-Supervised Representation Learning for 3D Point Clouds—0
Structural Relational Reasoning of Point Clouds—0
Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces—0
3DGTN: 3D Dual-Attention GLocal Transformer Network for Point Cloud Classification and Segmentation—0
3D Point Cloud Completion with Geometric-Aware Adversarial Augmentation—0
3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks—0
Text2Model: Text-based Model Induction for Zero-shot Image Classification—0
PointShuffleNet: Learning Non-Euclidean Features with Homotopy Equivalence and Mutual Information—0
A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation—0
Action Keypoint Network for Efficient Video Recognition—0
Adaptive Channel Encoding Transformer for Point Cloud Analysis—0
Adaptive Point Transformer—0
Adversarial Attack by Limited Point Cloud Surface Modifications—0
Adversarial Attacks and Defenses on 3D Point Cloud Classification: A Survey—0
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets—0
AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers—0
Airborne LiDAR Point Cloud Classification with Graph Attention Convolution Neural Network—0
A Learnable Self-supervised Task for Unsupervised Domain Adaptation on Point Clouds—0
A Network Architecture for Point Cloud Classification via Automatic Depth Images Generation—0
Adaptive Hierarchical Down-Sampling for Point Cloud Classification—0
PointWavelet: Learning in Spectral Domain for 3D Point Cloud Analysis—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