Exposing.ai
FFHQ

FFHQ

Flickr Faces High-Quality (FFHQ) is a dataset of photos used for face synthesis. The dataset was published in 2016 and contains 70,000 total images. Exposing.ai located 65,043 original photos from Flickr used to build FFHQ. The dataset has been used in at least 14 projects spanning 9 countries, including 6 projects that may have commercial applications.

FFHQ has recently become one of the most widely used datasets for generating fake faces. For example, the popular website ThisPersonDoesNotExist.com uses synthetic faces made from the FFHQ dataset.

Information Supply Chain

To help understand how FFHQ has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Flickr-Faces-HQ Dataset was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide an estimated overview of how and where images were used based on institutional affiliations. Thicker lines represent more citations. Please zoom in to see all institutions, as cities may have multiple points very close together.

FFHQ Copyright Distribution

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FFHQ Creative Commons license distribution | Download Data (CSV) | Download Chart (SVG)

FFHQ Creative Commons License Distribution

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FFHQ Creative Commons license distribution | Download Data (CSV) | Download Chart (SVG)

FFHQ Image Upload Year Distribution

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FFHQ Creative Commons license distribution | Download Data (CSV) | Download Chart (SVG)

Top 10 FFHQ Image #Tags

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Top 10 image #tags used in FFHQ | Download Data (CSV) | Download Chart (SVG)

Top 10 Geocoded Cities FFHQ

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Top 10 cities for geocoded photos in FFHQ | Download Data (CSV) | Download Chart (SVG)

Citing This Work

If you reference or use any data from the Exposing.ai project, cite our original research as follows:

@online{Exposing.ai,
  author = {Harvey, Adam. LaPlace, Jules.},
  title = {Exposing.ai},
  year = 2021,
  url = {https://exposing.ai},
  urldate = {2021-01-01}
}

If you reference or use any data from FFHQ cite the author's work:

@article{Karras2019ASG,
    author = "Karras, Tero and Laine, S. and Aila, Timo",
    title = "A Style-Based Generator Architecture for Generative Adversarial Networks",
    journal = "2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
    year = "2019",
    pages = "4396-4405"
}

References

  • 1 Tero Karras, et al. "A Style-Based Generator Architecture for Generative Adversarial Networks". 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). (2019): 4396-4405.