SOTAVerified

Point Cloud Classification

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

Papers

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Showing 181–190 of 265 papers

TitleStatusHype
Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation—0
Classification of Single-View Object Point Clouds—0
Temporal Reversed Training for Spiking Neural Networks with Generalized Spatio-Temporal Representation—0
Bridging Domain Gap of Point Cloud Representations via Self-Supervised Geometric Augmentation—0
Bridging the Gap: Point Clouds for Merging Neurons in Connectomics—0
CAP: Robust Point Cloud Classification via Semantic and Structural Modeling—0
CausalPC: Improving the Robustness of Point Cloud Classification by Causal Effect Identification—0
Classification of Aerial Photogrammetric 3D Point Clouds—0
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification—0
CLIP-based Point Cloud Classification via Point Cloud to Image Translation—0
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All datasetsPointCloud-CISPRS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PointNetmean Corruption Error (mCE)1.42—Unverified
2WOLFMix (PointNet)mean Corruption Error (mCE)1.18—Unverified
3PointNetmean Corruption Error (mCE)1.18—Unverified
4RSCNNmean Corruption Error (mCE)1.13—Unverified
5PAConvmean Corruption Error (mCE)1.1—Unverified
6SimpleViewmean Corruption Error (mCE)1.05—Unverified
7OcCo-DGCNNmean Corruption Error (mCE)1.05—Unverified
8PointMixUp (PointNet++)mean Corruption Error (mCE)1.03—Unverified
9DGCNNmean Corruption Error (mCE)1—Unverified
10OcCo-DGCNNmean Corruption Error (mCE)0.98—Unverified
#ModelMetricClaimedVerifiedStatus
1OursAverage F182.8—Unverified