SOTAVerified

Point Cloud Classification

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

Papers

Showing 150 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
Dynamic Local Feature Aggregation for Learning on Point CloudsCode1
ViewNet: A Novel Projection-Based Backbone With View Pooling for Few-Shot Point Cloud ClassificationCode1
Implicit Convolutional Kernels for Steerable CNNsCode1
TetraSphere: A Neural Descriptor for O(3)-Invariant Point Cloud AnalysisCode1
MATE: Masked Autoencoders are Online 3D Test-Time LearnersCode1
APSNet: Attention Based Point Cloud SamplingCode1
CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-trainingCode1
Rethinking the compositionality of point clouds through regularization in the hyperbolic spaceCode1
Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient ApproximationCode1
Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud UnderstandingCode1
Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classificationCode1
PointNorm: Dual Normalization is All You Need for Point Cloud AnalysisCode1
APP-Net: Auxiliary-point-based Push and Pull Operations for Efficient Point Cloud ClassificationCode1
Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit GradientsCode1
No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static Models by Fitting Feature-level Space-time SurfacesCode1
Visualizing Global Explanations of Point Cloud DNNsCode1
Quasi-Balanced Self-Training on Noise-Aware Synthesis of Object Point Clouds for Closing Domain GapCode1
3DCTN: 3D Convolution-Transformer Network for Point Cloud ClassificationCode1
LPF-Defense: 3D Adversarial Defense based on Frequency AnalysisCode1
Benchmarking and Analyzing Point Cloud Classification under CorruptionsCode1
Learnable Lookup Table for Neural Network QuantizationCode1
Why Discard if You Can Recycle?: A Recycling Max Pooling Module for 3D Point Cloud AnalysisCode1
Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point ModelingCode1
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point CloudsCode1
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation LearningCode1
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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