Flickr Faces HQ (FFHQ) 70K from StyleGAN
Tero Karras and Samuli Laine and Timo Aila

@article{,
title= {Flickr Faces HQ (FFHQ) 70K from StyleGAN},
journal= {CoRR},
author= {Tero Karras and Samuli Laine and Timo Aila},
year= {2018},
url= {https://github.com/NVlabs/ffhq-dataset/blob/93955b7cd435b7b1c724f8ca6a0e0c391300fe83/README.md},
abstract= {Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative adversarial networks (GAN). The dataset consists of 70,000 high-quality PNG images at 1024x1024 resolution and contains considerable variation in terms of age, ethnicity and image background. 

It also has good coverage of accessories such as eyeglasses, sunglasses, hats, etc. The images were crawled from Flickr, thus inheriting all the biases of that website, and automatically aligned and cropped using dlib. Only images under permissive licenses were collected. Various automatic filters were used to prune the set, and finally Amazon Mechanical Turk was used to remove the occasional statues, paintings, or photos of photos.},
keywords= {faces, GAN, stylegan, unsupervised, flickr, ffhq},
terms= {},
license= {The individual images were published in Flickr by their respective authors
under either Creative Commons BY 2.0, Creative Commons BY-NC 2.0,
Public Domain Mark 1.0, Public Domain CC0 1.0, or U.S. Government Works
license. All of these licenses allow free use, redistribution, and adaptation
for non-commercial purposes. However, some of them require giving appropriate
credit to the original author, as well as indicating any changes that were
made to the images. The license and original author of each image are
indicated in the metadata.

    https://creativecommons.org/licenses/by/2.0/
    https://creativecommons.org/licenses/by-nc/2.0/
    https://creativecommons.org/publicdomain/mark/1.0/
    https://creativecommons.org/publicdomain/zero/1.0/
    http://www.usa.gov/copyright.shtml

The dataset itself (including JSON metadata, download script, and
documentation) is made available under Creative Commons BY-NC-SA 4.0 license
by NVIDIA Corporation. You can use, redistribute, and adapt it for
non-commercial purposes, as long as you (a) give appropriate credit by
citing our paper, (b) indicate any changes that you've made, and
(c) distribute any derivative works under the same license.

    https://creativecommons.org/licenses/by-nc-sa/4.0/
},
superseded= {}
}