SOTAVerified

Point Cloud Classification

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

Papers

Showing 151160 of 265 papers

TitleStatusHype
Adaptive Channel Encoding Transformer for Point Cloud Analysis0
Bridging the Gap: Point Clouds for Merging Neurons in Connectomics0
CT-block: a novel local and global features extractor for point cloud0
Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point ModelingCode1
Imperceptible Transfer Attack and Defense on 3D Point Cloud Classification0
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point CloudsCode1
Two Heads are Better than One: Geometric-Latent Attention for Point Cloud Classification and SegmentationCode0
RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain AdaptationCode0
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation LearningCode1
PatchAugment: Local Neighborhood Augmentation in Point Cloud ClassificationCode0
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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