Qiong Cao, Li Shen, Weidi Xie, Omkar Parkhi, Andrew Zisserman


Overview

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.

9,000 + identities

VGGFace2 contains images from identities spanning a wide range of different ethnicities, accents, professions and ages.

Gender Distribution

3.3 million + faces

All face images are captured "in the wild", with pose and emotion variations and different lighting and occlusion conditions.

Train/Test Split

362 ~ per-subject samples

Face distribution for different identities is varied, from 87 to 843, with an average of 362 images for each subject.

Face Size Distribution

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We provide loosely-cropped faces for each identity, and meta information for each identity and each face image in the dataset. For each image, face detection and estimated 5 keypoints are provided.

Relevant Publications

[1] Q. Cao, L. Shen, W. Xie, O. M. Parkhi, A. Zisserman
International Conference on Automatic Face and Gesture Recognition, 2018

Acknowledgements

This research is based upon work supported by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via contract number 2014-14071600010. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of ODNI, IARPA, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purpose notwithstanding any copyright annotation thereon.