SOTAVerified

Point Cloud Classification

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

Papers

Showing 101110 of 265 papers

TitleStatusHype
CLIP-based Point Cloud Classification via Point Cloud to Image Translation0
FBPT: A Fully Binary Point Transformer0
Fourier Decomposition for Explicit Representation of 3D Point Cloud Attributes0
FatNet: A Feature-attentive Network for 3D Point Cloud Processing0
From depth image to semantic scene synthesis through point cloud classification and labeling: Application to assistive systems0
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets0
FA-KPConv: Introducing Euclidean Symmetries to KPConv via Frame Averaging0
CLR-GAM: Contrastive Point Cloud Learning with Guided Augmentation and Feature Mapping0
3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks0
Exploiting GPT-4 Vision for Zero-shot Point Cloud Understanding0
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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