SOTAVerified

Point Cloud Classification

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 191–200 of 265 papers

TitleStatusHype
S3I-PointHop: SO(3)-Invariant PointHop for 3D Point Cloud Classification—0
NPTC-net: Narrow-Band Parallel Transport Convolutional Neural Network on Point Clouds—0
On Learning the Right Attention Point for Feature Enhancement—0
On The Adversarial Robustness of 3D Point Cloud Classification—0
On Adversarial Robustness of 3D Point Cloud Classification under Adaptive Attacks—0
Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding—0
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency—0
OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization—0
Self-Distillation for Unsupervised 3D Domain Adaptation—0
Semantic-aware Transmission for Robust Point Cloud Classification—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