CelebA-align
2D Box
Classification
2D Keypoints
Face
|...
许可协议: Custom

Overview

CelebFaces Attributes Dataset (CelebA) is a large-scale face attributes dataset with more than 200K celebrity images, each with 40 attribute annotations. The images in this dataset cover large pose variations and background clutter. CelebA has large diversities, large quantities, and rich annotations, including

  • 10,177 number of identities,
  • 202,599 number of face aligned images
  • 5 landmark locations, 40 binary attributes annotations per image.

The dataset can be employed as the training and test sets for the following computer vision tasks: face attribute recognition, face detection, landmark (or facial part) localization, and face editing & synthesis.

Notes:

  1. Images are first roughly aligned using similarity transformation according to the two eye locations;
  2. Images are then resized to 218*178;

Citation

Please use the following citation when referencing the dataset:

@inproceedings{liu2015faceattributes,
 title = {Deep Learning Face Attributes in the Wild},
 author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
 booktitle = {Proceedings of International Conference on Computer Vision (ICCV)},
 month = {December},
 year = {2015}
}

License

Custom

数据概要
数据格式
Image,
数据量
202.599K
文件大小
--
发布方
CUHK Multimedia Lab
The CUHK Multimedia Lab (MMLab) is one of the pioneering institutes on deep learning. In GPU Technology Conference (GTC) 2016, a world-wide technology summit, our lab is recognized as one of the top ten AI pioneers, and listed together with top research groups in the world (e.g. MIT, Stanford, Berkeley, and Univ. of Toronto).
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