SOTAVerified

Point Cloud Classification

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

Papers

Showing 201210 of 265 papers

TitleStatusHype
PCT: Point cloud transformerCode1
Learning Category-level Shape Saliency via Deep Implicit Surface Networks0
On Learning the Right Attention Point for Feature Enhancement0
Sparse Convolutions on Continuous Domains for Point Cloud and Event Stream Networks0
On Adversarial Robustness of 3D Point Cloud Classification under Adaptive Attacks0
RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud ClassifiersCode1
MGIC: Multigrid-in-Channels Neural Network ArchitecturesCode0
Empowering Knowledge Distillation via Open Set Recognition for Robust 3D Point Cloud Classification0
PointManifold: Using Manifold Learning for Point Cloud Classification0
Unsupervised Point Cloud Pre-Training via Occlusion CompletionCode1
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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