SOTAVerified

Point Cloud Classification

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

Papers

Showing 5175 of 265 papers

TitleStatusHype
ModelNet-O: A Large-Scale Synthetic Dataset for Occlusion-Aware Point Cloud ClassificationCode1
MATE: Masked Autoencoders are Online 3D Test-Time LearnersCode1
MOPS-Net: A Matrix Optimization-driven Network forTask-Oriented 3D Point Cloud DownsamplingCode1
Collect-and-Distribute Transformer for 3D Point Cloud AnalysisCode1
A Closer Look at Few-Shot 3D Point Cloud ClassificationCode1
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point CloudsCode1
APSNet: Attention Based Point Cloud SamplingCode1
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point CloudsCode1
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation LearningCode1
Exploiting Inductive Bias in Transformer for Point Cloud Classification and SegmentationCode1
APP-Net: Auxiliary-point-based Push and Pull Operations for Efficient Point Cloud ClassificationCode1
Deep Declarative Networks: A New HopeCode1
Point Cloud Augmentation with Weighted Local TransformationsCode1
PointHop++: A Lightweight Learning Model on Point Sets for 3D ClassificationCode1
PointAugment: an Auto-Augmentation Framework for Point Cloud ClassificationCode1
Deep SetsCode1
Dynamic Local Feature Aggregation for Learning on Point CloudsCode1
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point CloudsCode1
Dense-Resolution Network for Point Cloud Classification and SegmentationCode1
Self-supervised Point Cloud Representation Learning via Separating Mixed ShapesCode1
Point Set Voting for Partial Point Cloud AnalysisCode1
Differentiable Euler Characteristic Transforms for Shape ClassificationCode1
Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and ClassificationCode1
Revisiting Point Cloud Shape Classification with a Simple and Effective BaselineCode1
Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient ApproximationCode1
Show:102550
← PrevPage 3 of 11Next →

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