SOTAVerified

Point Cloud Classification

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

Papers

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Showing 76–100 of 265 papers

TitleStatusHype
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point CloudCode1
Learnable Lookup Table for Neural Network QuantizationCode1
Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit GradientsCode1
Exploiting Inductive Bias in Transformer for Point Cloud Classification and SegmentationCode1
Dynamic Graph CNN for Learning on Point CloudsCode1
Dynamic Local Feature Aggregation for Learning on Point CloudsCode1
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient FlowsCode0
3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar dataCode0
Robustifying Point Cloud Networks by RefocusingCode0
Contrastive Embedding Distribution Refinement and Entropy-Aware Attention for 3D Point Cloud ClassificationCode0
Point-Voxel Adaptive Feature Abstraction for Robust Point Cloud ClassificationCode0
RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain AdaptationCode0
Boosting Point-BERT by Multi-choice TokensCode0
Unsupervised Feature Learning for Point Cloud by Contrasting and Clustering With Graph Convolutional Neural NetworkCode0
Point-PlaneNet: Plane kernel based convolutional neural network for point clouds analysisCode0
AGConv: Adaptive Graph Convolution on 3D Point CloudsCode0
Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional EncodingCode0
Classifying point clouds at the facade-level using geometric features and deep learning networksCode0
Classifying Objects in 3D Point Clouds Using Recurrent Neural Network: A GRU LSTM Hybrid ApproachCode0
PointDGMamba: Domain Generalization of Point Cloud Classification via Generalized State Space ModelCode0
PointManifoldCut: Point-wise Augmentation in the Manifold for Point CloudsCode0
Equivariant vs. Invariant Layers: A Comparison of Backbone and Pooling for Point Cloud ClassificationCode0
Adversarial shape perturbations on 3D point cloudsCode0
EPiC: Ensemble of Partial Point Clouds for Robust ClassificationCode0
PatchAugment: Local Neighborhood Augmentation in Point Cloud ClassificationCode0
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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