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 226–250 of 265 papers

TitleStatusHype
Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and ClassificationCode1
Triangle-Net: Towards Robustness in Point Cloud LearningCode0
PointAugment: an Auto-Augmentation Framework for Point Cloud ClassificationCode1
PointHop++: A Lightweight Learning Model on Point Sets for 3D ClassificationCode1
AdvectiveNet: An Eulerian-Lagrangian Fluidic reservoir for Point Cloud ProcessingCode0
Efficient and Stable Graph Scattering Transforms via Pruning—0
Geometry Sharing Network for 3D Point Cloud Classification and SegmentationCode0
Transductive Zero-Shot Learning for 3D Point Cloud ClassificationCode1
Grid-GCN for Fast and Scalable Point Cloud LearningCode0
SGAS: Sequential Greedy Architecture SearchCode0
Geometric Back-projection Network for Point Cloud ClassificationCode0
Learning Permutation Invariant Representations using Memory NetworksCode0
SRINet: Learning Strictly Rotation-Invariant Representations for Point Cloud Classification and Segmentation—0
Rotation Invariant Point Cloud Classification: Where Local Geometry Meets Global TopologyCode0
Density-Aware Convolutional Networks with Context Encoding for Airborne LiDAR Point Cloud Classification—0
Spherical Kernel for Efficient Graph Convolution on 3D Point CloudsCode0
Deep Declarative Networks: A New HopeCode1
Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud ClassificationCode0
Adversarial shape perturbations on 3D point cloudsCode0
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
ACNe: Attentive Context Normalization for Robust Permutation-Equivariant LearningCode0
Structural Relational Reasoning of Point Clouds—0
NPTC-net: Narrow-Band Parallel Transport Convolutional Neural Network on Point Clouds—0
Unsupervised Feature Learning for Point Cloud by Contrasting and Clustering With Graph Convolutional Neural NetworkCode0
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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