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 101–125 of 265 papers

TitleStatusHype
SA-MLP: A Low-Power Multiplication-Free Deep Network for 3D Point Cloud Classification in Resource-Constrained EnvironmentsCode0
Efficient Point Cloud Classification via Offline Distillation Framework and Negative-Weight Self-Distillation Technique—0
PMT-MAE: Dual-Branch Self-Supervised Learning with Distillation for Efficient Point Cloud Classification—0
PointDGMamba: Domain Generalization of Point Cloud Classification via Generalized State Space ModelCode0
Enhancing Sampling Protocol for Point Cloud Classification Against Corruptions—0
Temporal Reversed Training for Spiking Neural Networks with Generalized Spatio-Temporal Representation—0
CLIP-based Point Cloud Classification via Point Cloud to Image Translation—0
Rethinking Attention Module Design for Point Cloud Analysis—0
Boosting Cross-Domain Point Classification via Distilling Relational Priors from 2D TransformersCode0
Transferable 3D Adversarial Shape Completion using Diffusion ModelsCode0
Eidos: Efficient, Imperceptible Adversarial 3D Point Clouds—0
A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation—0
Leveraging PointNet and PointNet++ for Lyft Point Cloud Classification Challenge—0
CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction—0
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets—0
Meta Episodic learning with Dynamic Task Sampling for CLIP-based Point Cloud Classification—0
Image and Point-cloud Classification for Jet Analysis in High-Energy Physics: A survey—0
FBPT: A Fully Binary Point Transformer—0
Classifying Objects in 3D Point Clouds Using Recurrent Neural Network: A GRU LSTM Hybrid ApproachCode0
A Benchmark Grocery Dataset of Realworld Point Clouds From Single View—0
Classifying point clouds at the facade-level using geometric features and deep learning networksCode0
Adaptive Point Transformer—0
3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar dataCode0
Exploiting GPT-4 Vision for Zero-shot Point Cloud Understanding—0
Point Cloud Classification via Deep Set Linearized Optimal Transport—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