---
title: IMDB-Clean
canonical_url: "https://www.modelscope.cn/datasets/OmniData/IMDB-Clean"
md_url: "https://www.modelscope.cn/datasets/OmniData/IMDB-Clean.md"
repository: OmniData/IMDB-Clean
last_updated: 2024-07-02
license: "[IMDB-Clean Custom]"
storage_size: "81 MB"
domain:
  - publishDate
  - taskTypes
  - paperUrl
  - publishUrl
  - mediaTypes
  - displayName
  - publisher
tasks:
  - 2021
  - "Gender Bias Detection"
  - "https://arxiv.org/pdf/2106.11145v2.pdf"
  - "https://github.com/ibug-group/imdb-clean"
  - Image
  - IMDB-Clean
  - "Imperial College London"
downloads: 52
stars: 0
---

# IMDB-Clean

> IMDB-Clean - OmniData 在 ModelScope 开源的数据集。displayName: IMDB-Clean labelTypes: [] license: IMDB-Clean Custom mediaTypes: Image paperUrl: https://arxiv.org/pdf/2106.11145v2.pdf publishDate: "2021" publishUrl: https://github.com/ibug-group/imdb-clean publisher:…

OmniData/IMDB-Clean 是 ModelScope 魔搭社区上的2021、Gender Bias Detection、https://arxiv.org/pdf/2106.11145v2.pdf数据集，涉及 publishDate、taskTypes、paperUrl 领域，存储大小 81 MB，采用 [IMDB-Clean Custom] 许可。

- **Repository**: OmniData/IMDB-Clean
- **License**: [IMDB-Clean Custom]
- **Tasks**: 2021, Gender Bias Detection, https://arxiv.org/pdf/2106.11145v2.pdf, https://github.com/ibug-group/imdb-clean, Image, IMDB-Clean, Imperial College London
- **Domain**: publishDate, taskTypes, paperUrl, publishUrl, mediaTypes, displayName, publisher
- **Storage size**: 81 MB
- **Downloads**: 52
- **Stars**: 0
- **Last updated**: 2024-07-02

Source: https://www.modelscope.cn/datasets/OmniData/IMDB-Clean

---

displayName: IMDB-Clean
labelTypes: []
license:
- IMDB-Clean Custom
mediaTypes:
- Image
paperUrl: https://arxiv.org/pdf/2106.11145v2.pdf
publishDate: "2021"
publishUrl: https://github.com/ibug-group/imdb-clean
publisher:
- Imperial College London
tags:
- Human face
- Human
taskTypes:
- Face Recognition
- Age Estimation
- Facial Attribute Classification
- Age And Gender Classification
- Gender Prediction
- Gender Bias Detection

---
# 数据集介绍
  ## 简介
  我们使用约束聚类方法清理了嘈杂的 IMDB-WIKI 数据集，从而产生了这个用于野外年龄估计的新基准。注释还允许该数据集用于其他一些任务，例如性别分类和面部识别/验证。有关详细信息，请参阅我们的 FPAge 论文。
  ## 引文
  ```
@article{lin2022fp,
  title={FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild},
  author={Lin, Yiming and Shen, Jie and Wang, Yujiang and Pantic, Maja},
  journal={IEEE Transactions on Image Processing},
  year={2022},
  publisher={IEEE}
}
```
  
## Download dataset
:modelscope-code[]{type="git"}