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celeb_a

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 images, and - 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, and landmark (or facial part) localization.

Split Examples
'test' 19,962
'train' 162,770
'validation' 19,867
  • Feature structure:
FeaturesDict({
    'attributes': FeaturesDict({
        '5_o_Clock_Shadow': tf.bool,
        'Arched_Eyebrows': tf.bool,
        'Attractive': tf.bool,
        'Bags_Under_Eyes': tf.bool,
        'Bald': tf.bool,
        'Bangs': tf.bool,
        'Big_Lips': tf.bool,
        'Big_Nose': tf.bool,
        'Black_Hair': tf.bool,
        'Blond_Hair': tf.bool,
        'Blurry': tf.bool,
        'Brown_Hair': tf.bool,
        'Bushy_Eyebrows': tf.bool,
        'Chubby': tf.bool,
        'Double_Chin': tf.bool,
        'Eyeglasses': tf.bool,
        'Goatee': tf.bool,
        'Gray_Hair': tf.bool,
        'Heavy_Makeup': tf.bool,
        'High_Cheekbones': tf.bool,
        'Male': tf.bool,
        'Mouth_Slightly_Open': tf.bool,
        'Mustache': tf.bool,
        'Narrow_Eyes': tf.bool,
        'No_Beard': tf.bool,
        'Oval_Face': tf.bool,
        'Pale_Skin': tf.bool,
        'Pointy_Nose': tf.bool,
        'Receding_Hairline': tf.bool,
        'Rosy_Cheeks': tf.bool,
        'Sideburns': tf.bool,
        'Smiling': tf.bool,
        'Straight_Hair': tf.bool,
        'Wavy_Hair': tf.bool,
        'Wearing_Earrings': tf.bool,
        'Wearing_Hat': tf.bool,
        'Wearing_Lipstick': tf.bool,
        'Wearing_Necklace': tf.bool,
        'Wearing_Necktie': tf.bool,
        'Young': tf.bool,
    }),
    'image': Image(shape=(218, 178, 3), dtype=tf.uint8),
    'landmarks': FeaturesDict({
        'lefteye_x': tf.int64,
        'lefteye_y': tf.int64,
        'leftmouth_x': tf.int64,
        'leftmouth_y': tf.int64,
        'nose_x': tf.int64,
        'nose_y': tf.int64,
        'righteye_x': tf.int64,
        'righteye_y': tf.int64,
        'rightmouth_x': tf.int64,
        'rightmouth_y': tf.int64,
    }),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
attributes FeaturesDict
attributes/5_o_Clock_Shadow Tensor tf.bool
attributes/Arched_Eyebrows Tensor tf.bool
attributes/Attractive Tensor tf.bool
attributes/Bags_Under_Eyes Tensor tf.bool
attributes/Bald Tensor tf.bool
attributes/Bangs Tensor tf.bool
attributes/Big_Lips Tensor tf.bool
attributes/Big_Nose Tensor tf.bool
attributes/Black_Hair Tensor tf.bool
attributes/Blond_Hair Tensor tf.bool
attributes/Blurry Tensor tf.bool
attributes/Brown_Hair Tensor tf.bool
attributes/Bushy_Eyebrows Tensor tf.bool
attributes/Chubby Tensor tf.bool
attributes/Double_Chin Tensor tf.bool
attributes/Eyeglasses Tensor tf.bool
attributes/Goatee Tensor tf.bool
attributes/Gray_Hair Tensor tf.bool
attributes/Heavy_Makeup Tensor tf.bool
attributes/High_Cheekbones Tensor tf.bool
attributes/Male Tensor tf.bool
attributes/Mouth_Slightly_Open Tensor tf.bool
attributes/Mustache Tensor tf.bool
attributes/Narrow_Eyes Tensor tf.bool
attributes/No_Beard Tensor tf.bool
attributes/Oval_Face Tensor tf.bool
attributes/Pale_Skin Tensor tf.bool
attributes/Pointy_Nose Tensor tf.bool
attributes/Receding_Hairline Tensor tf.bool
attributes/Rosy_Cheeks Tensor tf.bool
attributes/Sideburns Tensor tf.bool
attributes/Smiling Tensor tf.bool
attributes/Straight_Hair Tensor tf.bool
attributes/Wavy_Hair Tensor tf.bool
attributes/Wearing_Earrings Tensor tf.bool
attributes/Wearing_Hat Tensor tf.bool
attributes/Wearing_Lipstick Tensor tf.bool
attributes/Wearing_Necklace Tensor tf.bool
attributes/Wearing_Necktie Tensor tf.bool
attributes/Young Tensor tf.bool
image Image (218, 178, 3) tf.uint8
landmarks FeaturesDict
landmarks/lefteye_x Tensor tf.int64
landmarks/lefteye_y Tensor tf.int64
landmarks/leftmouth_x Tensor tf.int64
landmarks/leftmouth_y Tensor tf.int64
landmarks/nose_x Tensor tf.int64
landmarks/nose_y Tensor tf.int64
landmarks/righteye_x Tensor tf.int64
landmarks/righteye_y Tensor tf.int64
landmarks/rightmouth_x Tensor tf.int64
landmarks/rightmouth_y Tensor tf.int64

Visualization

  • Citation:
@inproceedings{conf/iccv/LiuLWT15,
  added-at = {2018-10-09T00:00:00.000+0200},
  author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
  biburl = {https://www.bibsonomy.org/bibtex/250e4959be61db325d2f02c1d8cd7bfbb/dblp},
  booktitle = {ICCV},
  crossref = {conf/iccv/2015},
  ee = {http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.425},
  interhash = {3f735aaa11957e73914bbe2ca9d5e702},
  intrahash = {50e4959be61db325d2f02c1d8cd7bfbb},
  isbn = {978-1-4673-8391-2},
  keywords = {dblp},
  pages = {3730-3738},
  publisher = {IEEE Computer Society},
  timestamp = {2018-10-11T11:43:28.000+0200},
  title = {Deep Learning Face Attributes in the Wild.},
  url = {http://dblp.uni-trier.de/db/conf/iccv/iccv2015.html#LiuLWT15},
  year = 2015
}