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  • Description:

VGGFace2 is a large-scale face recognition dataset. Images are downloaded from Google Image Search and have large variations in pose, age, illumination, ethnicity and profession. VGGFace2 contains images from identities spanning a wide range of different ethnicities, accents, professions and ages. All face images are captured "in the wild", with pose and emotion variations and different lighting and occlusion conditions. Face distribution for different identities is varied, from 87 to 843, with an average of 362 images for each subject.

Split Examples
'test' 169,396
'train' 3,141,890
  • Features:
    'file_name': Text(shape=(), dtype=tf.string),
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=9131),


  • Citation:
author = "Cao, Q. and Shen, L. and Xie, W. and Parkhi, O. M. and Zisserman, A.",
title  = "VGGFace2: A dataset for recognising faces across pose and age",
booktitle = "International Conference on Automatic Face and Gesture Recognition",
year  = "2018"}