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 1–25 of 265 papers

TitleStatusHype
Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud LearningCode3
FRACTAL: An Ultra-Large-Scale Aerial Lidar Dataset for 3D Semantic Segmentation of Diverse LandscapesCode3
Curvature Diversity-Driven Deformation and Domain Alignment for Point CloudCode2
Frozen Transformers in Language Models Are Effective Visual Encoder LayersCode2
Point Transformer V2: Grouped Vector Attention and Partition-based PoolingCode2
Beyond Self-attention: External Attention using Two Linear Layers for Visual TasksCode2
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point CloudsCode1
Spiking Point Transformer for Point Cloud ClassificationCode1
Point-GN: A Non-Parametric Network Using Gaussian Positional Encoding for Point Cloud ClassificationCode1
Test-Time Adaptation in Point Clouds: Leveraging Sampling Variation with Weight AveragingCode1
PointNet with KAN versus PointNet with MLP for 3D Classification and Segmentation of Point SetsCode1
Robust 3D Point Clouds Classification based on Declarative DefendersCode1
Positional Prompt Tuning for Efficient 3D Representation LearningCode1
RISurConv: Rotation Invariant Surface Attention-Augmented Convolutions for 3D Point Cloud Classification and SegmentationCode1
Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point CloudsCode1
ModelNet-O: A Large-Scale Synthetic Dataset for Occlusion-Aware Point Cloud ClassificationCode1
Differentiable Euler Characteristic Transforms for Shape ClassificationCode1
Robust Point Cloud Processing through Positional EmbeddingCode1
Risk-optimized Outlier Removal for Robust 3D Point Cloud ClassificationCode1
Collect-and-Distribute Transformer for 3D Point Cloud AnalysisCode1
SUG: Single-dataset Unified Generalization for 3D Point Cloud ClassificationCode1
Exploiting Inductive Bias in Transformer for Point Cloud Classification and SegmentationCode1
A Closer Look at Few-Shot 3D Point Cloud ClassificationCode1
What Makes for Effective Few-shot Point Cloud Classification?Code1
Point Cloud Classification Using Content-based Transformer via Clustering in Feature SpaceCode1
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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