SOTAVerified

Point Cloud Classification

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

Papers

Showing 51100 of 265 papers

TitleStatusHype
Point Cloud Augmentation with Weighted Local TransformationsCode1
Self-supervised Point Cloud Representation Learning via Separating Mixed ShapesCode1
Geometry-Aware Self-Training for Unsupervised Domain Adaptationon Object Point CloudsCode1
Surrogate Model-Based Explainability Methods for Point Cloud NNsCode1
Revisiting Point Cloud Shape Classification with a Simple and Effective BaselineCode1
Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained ModelsCode1
Walk in the Cloud: Learning Curves for Point Clouds Shape AnalysisCode1
Zero-Shot Learning on 3D Point Cloud Objects and BeyondCode1
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point CloudsCode1
Regularization Strategy for Point Cloud via Rigidly Mixed SampleCode1
PointCutMix: Regularization Strategy for Point Cloud ClassificationCode1
Revisiting Point Cloud Classification with a Simple and Effective BaselineCode1
Geometry-Aware Self-Training for Unsupervised Domain Adaptation on Object Point CloudsCode1
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point CloudCode1
PCT: Point cloud transformerCode1
RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud ClassifiersCode1
Unsupervised Point Cloud Pre-Training via Occlusion CompletionCode1
PointMixup: Augmentation for Point CloudsCode1
Point Set Voting for Partial Point Cloud AnalysisCode1
Parameter-Efficient Person Re-identification in the 3D SpaceCode1
Dense-Resolution Network for Point Cloud Classification and SegmentationCode1
MOPS-Net: A Matrix Optimization-driven Network forTask-Oriented 3D Point Cloud DownsamplingCode1
Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and ClassificationCode1
PointAugment: an Auto-Augmentation Framework for Point Cloud ClassificationCode1
PointHop++: A Lightweight Learning Model on Point Sets for 3D ClassificationCode1
Transductive Zero-Shot Learning for 3D Point Cloud ClassificationCode1
Deep Declarative Networks: A New HopeCode1
Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World DataCode1
PointHop: An Explainable Machine Learning Method for Point Cloud ClassificationCode1
Dynamic Graph CNN for Learning on Point CloudsCode1
Deep SetsCode1
BeyondRPC: A Contrastive and Augmentation-Driven Framework for Robust Point Cloud UnderstandingCode0
Rethinking Gradient-based Adversarial Attacks on Point Cloud Classification0
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency0
Hybrid-Emba3D: Geometry-Aware and Cross-Path Feature Hybrid Enhanced State Space Model for Point Cloud ClassificationCode0
Streaming Sliced Optimal TransportCode0
FA-KPConv: Introducing Euclidean Symmetries to KPConv via Frame Averaging0
DG-MVP: 3D Domain Generalization via Multiple Views of Point Clouds for Classification0
Introducing the Short-Time Fourier Kolmogorov Arnold Network: A Dynamic Graph CNN Approach for Tree Species Classification in 3D Point CloudsCode0
Fourier Decomposition for Explicit Representation of 3D Point Cloud Attributes0
RS2AD: End-to-End Autonomous Driving Data Generation from Roadside Sensor Observations0
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient FlowsCode0
Token Adaptation via Side Graph Convolution for Temporally and Spatially Efficient Fine-tuning of 3D Point Cloud TransformersCode0
AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers0
OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization0
Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional EncodingCode0
RW-Net: Enhancing Few-Shot Point Cloud Classification with a Wavelet Transform Projection-based Network0
STREAM: A Universal State-Space Model for Sparse Geometric Data0
Low-Density 3D Point Cloud Classification0
Bridging Domain Gap of Point Cloud Representations via Self-Supervised Geometric Augmentation0
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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