SOTAVerified

3D Point Cloud Classification

Papers

Showing 126–150 of 202 papers

TitleStatusHype
Self-supervised Point Cloud Representation Learning via Separating Mixed ShapesCode1
Learning Inner-Group Relations on Point CloudsCode1
Dual-Neighborhood Deep Fusion Network for Point Cloud Analysis—0
Adaptive Graph Convolution for Point Cloud AnalysisCode0
PVT: Point-Voxel Transformer for Point Cloud LearningCode1
Point Discriminative Learning for Data-efficient 3D Point Cloud Analysis—0
MKConv: Multidimensional Feature Representation for Point Cloud Analysis—0
Rotation Transformation Network: Learning View-Invariant Point Cloud for Classification and SegmentationCode0
Training or Architecture? How to Incorporate Invariance in Neural Networks—0
Revisiting Point Cloud Shape Classification with a Simple and Effective BaselineCode1
Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained ModelsCode1
Walk in the Cloud: Learning Curves for Point Clouds Shape AnalysisCode1
Dual Transformer for Point Cloud Analysis—0
Zero-Shot Learning on 3D Point Cloud Objects and BeyondCode1
Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks—0
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point CloudsCode1
PointGuard: Provably Robust 3D Point Cloud Classification—0
Perceiver: General Perception with Iterative AttentionCode1
Regularization Strategy for Point Cloud via Rigidly Mixed SampleCode1
PointCutMix: Regularization Strategy for Point Cloud ClassificationCode1
Revisiting Point Cloud Classification with a Simple and Effective BaselineCode1
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point CloudCode1
PCT: Point cloud transformerCode1
FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware ModellingCode1
Point TransformerCode1
Show:102550
← PrevPage 6 of 9Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PointGSTOverall Accuracy95.3—Unverified
2Mamba3D + Point-MAEOverall Accuracy95.1—Unverified
3ReCon++Overall Accuracy95—Unverified
4PointGPTOverall Accuracy94.9—Unverified
5point2vecOverall Accuracy94.8—Unverified
6RepSurf-UOverall Accuracy94.7—Unverified
7ReConOverall Accuracy94.7—Unverified
8ULIP + PointMLPOverall Accuracy94.7—Unverified
9AsymDSD-B* (no voting)Overall Accuracy94.7—Unverified
10PointMLP+HyCoReOverall Accuracy94.5—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniVec2Overall Accuracy97.2—Unverified
2PointGSTOverall Accuracy96.18—Unverified
3OmniVecOverall Accuracy96.1—Unverified
4GPSFormerOverall Accuracy95.4—Unverified
5ReCon++Overall Accuracy95.25—Unverified
6AsymDSD-B* (no voting)Overall Accuracy93.72—Unverified
7PointGPTOverall Accuracy93.4—Unverified
8GPSFormer-eliteOverall Accuracy93.3—Unverified
9Mamba3DOverall Accuracy92.64—Unverified
10Mamba3D (no voting)Overall Accuracy91.81—Unverified
#ModelMetricClaimedVerifiedStatus
1PointNetError Rate0.28—Unverified
2SimpleViewError Rate0.27—Unverified
3RSCNNError Rate0.26—Unverified
4DGCNNError Rate0.26—Unverified
5PCTError Rate0.26—Unverified
6PointNet++Error Rate0.24—Unverified
7PointNet++/+PointMixupError Rate0.19—Unverified
8PointNet++/+PointCutMix-RError Rate0.19—Unverified
9PCT+RSMixError Rate0.17—Unverified
10DGCNN+PointCutMix-RError Rate0.17—Unverified