ModelNet40-C

We create the ModelNet40-C dataset, which contains 185,100 point clouds from 40 classes, 15 corruption types, and 5 severity levels. We provide a detailed taxonomy of the constructed corruption types. ModelNet40-C is, to the best of our knowledge, the first comprehensive dataset for benchmarking corruption robustness of 3D point cloud classification. This dataset is from our arXiv paper: Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions.

本研究构建了ModelNet40-C数据集，该数据集包含40个类别、15种干扰类型与5种强度等级下的共计185100个点云数据。我们为所构建的干扰类型提供了详细的分类体系。据我们所知，ModelNet40-C是首个用于评测3D点云分类任务抗干扰鲁棒性的综合基准数据集。本数据集源自我们发表于arXiv预印本平台的论文《Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions》。

搜集汇总

背景与挑战

背景概述

ModelNet40-C是一个用于3D点云分类损坏鲁棒性基准测试的数据集，包含185,100个点云，涵盖40个类别、15种损坏类型和5个严重级别。该数据集由多机构研究人员创建，旨在评估模型在常见损坏下的性能，是首个全面的3D点云损坏鲁棒性基准数据集。