SOTAVerified

Point Cloud Classification

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

Papers

Showing 181190 of 265 papers

TitleStatusHype
Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding0
DuMLP-Pin: A Dual-MLP-dot-product Permutation-invariant Network for Set Feature ExtractionCode0
Contrastive Embedding Distribution Refinement and Entropy-Aware Attention for 3D Point Cloud ClassificationCode0
Action Keypoint Network for Efficient Video Recognition0
On Automatic Data Augmentation for 3D Point Cloud ClassificationCode0
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
Imperceptible Transfer Attack and Defense on 3D Point Cloud Classification0
Two Heads are Better than One: Geometric-Latent Attention for Point Cloud Classification and SegmentationCode0
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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