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Point Cloud Classification On Pointcloud C

Metrics

mean Corruption Error (mCE)

Results

Performance results of various models on this benchmark

Paper Title
PointNet1.422PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
WOLFMix (PointNet)1.180Benchmarking and Analyzing Point Cloud Classification under Corruptions
RSCNN1.130Relation-Shape Convolutional Neural Network for Point Cloud Analysis
PAConv1.104PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
SimpleView1.047Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
OcCo-DGCNN1.047Unsupervised Point Cloud Pre-Training via Occlusion Completion
PointMixUp (PointNet++)1.028PointMixup: Augmentation for Point Clouds
DGCNN1.000Dynamic Graph CNN for Learning on Point Clouds
CurveNet0.927Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis
PCT0.925PCT: Point cloud transformer
GDANet0.892Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud
RPC0.863Benchmarking and Analyzing Point Cloud Classification under Corruptions
PointWOLF (DGCNN)0.814Point Cloud Augmentation with Weighted Local Transformations
RSMix (DGCNN)0.745Regularization Strategy for Point Cloud via Rigidly Mixed Sample
WOLFMix (RPC)0.601Benchmarking and Analyzing Point Cloud Classification under Corruptions
WOLFMix (DGCNN)0.590Benchmarking and Analyzing Point Cloud Classification under Corruptions
WOLFMix (GDANet)0.571Benchmarking and Analyzing Point Cloud Classification under Corruptions
EPiC(GDANet+WOLFMix)0.530EPiC: Ensemble of Partial Point Clouds for Robust Classification
EPiC (DGCNN+WOLFMix)0.529EPiC: Ensemble of Partial Point Clouds for Robust Classification
EPiC (PCT+WOLFMix)0.510EPiC: Ensemble of Partial Point Clouds for Robust Classification
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Point Cloud Classification On Pointcloud C | SOTA | HyperAI