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 141–150 of 265 papers

TitleStatusHype
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
PMT-MAE: Dual-Branch Self-Supervised Learning with Distillation for Efficient Point Cloud Classification—0
Shape-Oriented Convolution Neural Network for Point Cloud Analysis—0
PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples—0
PointCert: Point Cloud Classification with Deterministic Certified Robustness Guarantees—0
Transformers in Vision: A Survey—0
Point Cloud Classification via Deep Set Linearized Optimal Transport—0
Sparse Convolutions on Continuous Domains for Point Cloud and Event Stream Networks—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