---
title: ModelNet40-C
canonical_url: "https://www.modelscope.cn/datasets/OmniData/ModelNet40-C"
md_url: "https://www.modelscope.cn/datasets/OmniData/ModelNet40-C.md"
repository: OmniData/ModelNet40-C
last_updated: 2024-07-09
license: "[BSD 3-Clause]"
storage_size: "2.1 GB"
domain:
  - publishDate
  - taskTypes
  - paperUrl
  - publishUrl
  - publisher
  - displayName
  - mediaTypes
tasks:
  - 2022-01-28
  - "3D Classification"
  - "https://arxiv.org/pdf/2201.12296v1.pdf"
  - "https://sites.google.com/umich.edu/modelnet40c"
  - "Lawrence Livermore National Laboratory"
  - "ModelNet40-C (ModelNet-C)"
  - PointCloud
downloads: 1314
stars: 0
---

# ModelNet40-C

> ModelNet40-C - OmniData 在 ModelScope 开源的数据集。displayName: ModelNet40-C (ModelNet-C) labelTypes: [] license: BSD 3-Clause mediaTypes: PointCloud paperUrl: https://arxiv.org/pdf/2201.12296v1.pdf publishDate: "2022-01-28" publishUrl:…

OmniData/ModelNet40-C 是 ModelScope 魔搭社区上的2022-01-28、3D Classification、https://arxiv.org/pdf/2201.12296v1.pdf数据集，涉及 publishDate、taskTypes、paperUrl 领域，存储大小 2.1 GB，采用 [BSD 3-Clause] 许可。

- **Repository**: OmniData/ModelNet40-C
- **License**: [BSD 3-Clause]
- **Tasks**: 2022-01-28, 3D Classification, https://arxiv.org/pdf/2201.12296v1.pdf, https://sites.google.com/umich.edu/modelnet40c, Lawrence Livermore National Laboratory, ModelNet40-C (ModelNet-C), PointCloud
- **Domain**: publishDate, taskTypes, paperUrl, publishUrl, publisher, displayName, mediaTypes
- **Storage size**: 2.1 GB
- **Downloads**: 1314
- **Stars**: 0
- **Last updated**: 2024-07-09

Source: https://www.modelscope.cn/datasets/OmniData/ModelNet40-C

---

displayName: ModelNet40-C (ModelNet-C)
labelTypes: []
license:
- BSD 3-Clause
mediaTypes:
- PointCloud
paperUrl: https://arxiv.org/pdf/2201.12296v1.pdf
publishDate: "2022-01-28"
publishUrl: https://sites.google.com/umich.edu/modelnet40c
publisher:
- University of Michigan
- NVIDIA
- Arizona State University
- Lawrence Livermore National Laboratory
tags: []
taskTypes:
- 3D Point Cloud Classification
- Robust Classification
- 3D Classification

---
  ## 简介
  ModelNet40-C 是一个综合数据集，用于对 3D 点云识别的损坏鲁棒性进行基准测试。
我们基于 ModelNet40 验证集创建 ModelNet40-C，该验证集具有 15 种损坏类型和每种损坏类型的 5 个严重级别，包括密度、噪声和转换损坏模式。我们的数据集包含 185,000 个不同的点云，有助于全面了解模型的稳健性。
  ## 引文
  ```
@article{sun2022benchmarking,
  title={Benchmarking robustness of 3d point cloud recognition against common corruptions},
  author={Sun, Jiachen and Zhang, Qingzhao and Kailkhura, Bhavya and Yu, Zhiding and Xiao, Chaowei and Mao, Z Morley},
  journal={arXiv preprint arXiv:2201.12296},
  year={2022}
}
```
  
## Download dataset
:modelscope-code[]{type="git"}