PointCloud-C

Overview edit

Variants: PointCloud-C

Associated Benchmarks

This dataset is used in 2 benchmarks:

• Point Cloud Classification - Metrics: mean Corruption Error (mCE)
• Point Cloud Segmentation - Metrics: mean Corruption Error (mCE)

Recent Benchmark Submissions

Research Papers

Recent papers with results on this dataset:

• Robustifying Point Cloud Networks by Refocusing (2023) -
• EPiC: Ensemble of Partial Point Clouds for Robust Classification (2023) -
• Masked Autoencoders for Point Cloud Self-supervised Learning (2022) -
• Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework (2022) -
• Benchmarking and Analyzing Point Cloud Classification under Corruptions (2022) -
• Point Cloud Augmentation with Weighted Local Transformations (2021) -
• Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline (2021) -
• Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis (2021) -
• PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds (2021) -
• Regularization Strategy for Point Cloud via Rigidly Mixed Sample (2021) -
• Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud (2020) -
• PCT: Point cloud transformer (2020) -
• Point Transformer (2020) -
• Unsupervised Point Cloud Pre-Training via Occlusion Completion (2020) -
• PointMixup: Augmentation for Point Clouds (2020) -
• Relation-Shape Convolutional Neural Network for Point Cloud Analysis (2019) -
• Dynamic Graph CNN for Learning on Point Clouds (2018) -
• PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space (2017) -
• PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (2016) -