SOTAVerified

3D Point Cloud Classification

Papers

Showing 5175 of 202 papers

TitleStatusHype
Decoupled Local Aggregation for Point Cloud LearningCode1
3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud AnalysisCode1
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable PoolingCode1
P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel PromptingCode1
Parameter-Efficient Person Re-identification in the 3D SpaceCode1
Point2Vec for Self-Supervised Representation Learning on Point CloudsCode1
APSNet: Attention Based Point Cloud SamplingCode1
PCT: Point cloud transformerCode1
FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware ModellingCode1
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point CloudCode1
PointCutMix: Regularization Strategy for Point Cloud ClassificationCode1
Point TransformerCode1
Point-GN: A Non-Parametric Network Using Gaussian Positional Encoding for Point Cloud ClassificationCode1
Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point ModelingCode1
Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained ModelsCode1
Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point CloudsCode1
APP-Net: Auxiliary-point-based Push and Pull Operations for Efficient Point Cloud ClassificationCode1
Point Cloud Classification Using Content-based Transformer via Clustering in Feature SpaceCode1
A Closer Look at Few-Shot 3D Point Cloud ClassificationCode1
Implicit Autoencoder for Point-Cloud Self-Supervised Representation LearningCode1
Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative PretrainingCode1
Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud ModelsCode1
GPSFormer: A Global Perception and Local Structure Fitting-based Transformer for Point Cloud UnderstandingCode1
Learning Inner-Group Relations on Point CloudsCode1
Learning to SampleCode1
Show:102550
← PrevPage 3 of 9Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PointGSTOverall Accuracy95.3Unverified
2Mamba3D + Point-MAEOverall Accuracy95.1Unverified
3ReCon++Overall Accuracy95Unverified
4PointGPTOverall Accuracy94.9Unverified
5point2vecOverall Accuracy94.8Unverified
6RepSurf-UOverall Accuracy94.7Unverified
7ReConOverall Accuracy94.7Unverified
8ULIP + PointMLPOverall Accuracy94.7Unverified
9AsymDSD-B* (no voting)Overall Accuracy94.7Unverified
10PointMLP+HyCoReOverall Accuracy94.5Unverified
#ModelMetricClaimedVerifiedStatus
1OmniVec2Overall Accuracy97.2Unverified
2PointGSTOverall Accuracy96.18Unverified
3OmniVecOverall Accuracy96.1Unverified
4GPSFormerOverall Accuracy95.4Unverified
5ReCon++Overall Accuracy95.25Unverified
6AsymDSD-B* (no voting)Overall Accuracy93.72Unverified
7PointGPTOverall Accuracy93.4Unverified
8GPSFormer-eliteOverall Accuracy93.3Unverified
9Mamba3DOverall Accuracy92.64Unverified
10Mamba3D (no voting)Overall Accuracy91.81Unverified
#ModelMetricClaimedVerifiedStatus
1PointNetError Rate0.28Unverified
2SimpleViewError Rate0.27Unverified
3RSCNNError Rate0.26Unverified
4DGCNNError Rate0.26Unverified
5PCTError Rate0.26Unverified
6PointNet++Error Rate0.24Unverified
7PointNet++/+PointMixupError Rate0.19Unverified
8PointNet++/+PointCutMix-RError Rate0.19Unverified
9PCT+RSMixError Rate0.17Unverified
10DGCNN+PointCutMix-RError Rate0.17Unverified