SOTAVerified

Point Cloud Classification

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

Papers

Showing 231240 of 265 papers

TitleStatusHype
Cloud Transformers: A Universal Approach To Point Cloud Processing Tasks0
Point-PlaneNet: Plane kernel based convolutional neural network for point clouds analysisCode0
Shape-Oriented Convolution Neural Network for Point Cloud Analysis0
Airborne LiDAR Point Cloud Classification with Graph Attention Convolution Neural Network0
Triangle-Net: Towards Robustness in Point Cloud LearningCode0
AdvectiveNet: An Eulerian-Lagrangian Fluidic reservoir for Point Cloud ProcessingCode0
Efficient and Stable Graph Scattering Transforms via Pruning0
Geometry Sharing Network for 3D Point Cloud Classification and SegmentationCode0
Grid-GCN for Fast and Scalable Point Cloud LearningCode0
SGAS: Sequential Greedy Architecture SearchCode0
Show:102550
← PrevPage 24 of 27Next →

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