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YFCC100M: The New Data in Multimedia Research

Paper · 2015 · Bart Thomee, David A. Shamma, Gerald Friedland et al.

Summary

Multimedia research has mostly relied on small, single-purpose collections. These often contain only one media type, are seldom shared, and are sometimes gathered without regard to licensing. The result is poor reproducibility and little reuse across projects. The authors address this by releasing YFCC100M (Yahoo Flickr Creative Commons 100 Million) through the Yahoo Webscope program. It covers 100 million Flickr photos and videos uploaded between 2004 and 2014, all published under Creative Commons licenses, so academia and industry can use them legally.

The core release is metadata only, distributed via Amazon AWS. Each item includes:

  • user and camera,
  • capture and upload times,
  • optional geolocation and license,
  • title, description, and tags,
  • links to the item on Flickr.

The authors plan "expansion packs" with extracted features, detected visual concepts, Exif data, and the media files themselves. They also profile the collection's tags, time span, locations, and cameras, and outline research directions it enables: visual recognition, spatiotemporal event analysis, and digital culture and preservation. The paper matters because it gives researchers a common, legally shareable, very large benchmark resource.

Key points

  • YFCC100M has about 99.2M photos and 0.8M videos. The metadata archive is 12.5GB compressed. Social signals such as comments, favorites, and followers are left out because they change constantly.
  • User tags are present on 68,552,616 photos and 418,507 videos. Machine-generated tags appear on 3,343,487 photos and 7,281 videos.
  • Roughly half of the items are geotagged (48,366,323 photos and 103,506 videos). They span 249 territories. Six cities draw contributions from more than 10,000 users each: Hong Kong, Tokyo, London, New York, Paris, and San Francisco.
  • The 25 most common cameras are mostly DSLRs, with the Canon EOS 400D at the top (≈2.54M photos). Apple iPhone models are the only exception in this list.
  • Visual and aural features have already been released as add-ons. The authors stress CC license compliance, attribution rules, and guidelines for reproducible experiments.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🔬International Computer Science InstituteBerkeley · United States18 works · 16,608 citations🏢YahooSunnyvale · United States8 works · 11,973 citations🔬Lawrence Livermore National LaboratoryLivermore · United States6 works · 2,127 citations

 Fields, topics and concepts

📚 Shelves 2The field of science this work belongs to (OpenAlex fields).Computer Science · 18,614 worksComputer Vision and Pattern Recognition · 3,486 works

Cite

Cite as Bart Thomee, David A. Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth and Li-Jia Li. 2015. YFCC100M: The New Data in Multimedia Research. arXiv:1503.01817 · Communications of the ACM, 59(2), pp. 64-73, 2016.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.1145/2812802 · arXiv 1503.01817

@misc{thomee2015yfcc100m,
  title = {{YFCC100M: The New Data in Multimedia Research}},
  author = {Bart Thomee, David A. Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth and Li-Jia Li},
  year = {2015},
  doi = {10.1145/2812802},
  eprint = {1503.01817},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.1145/2812802}
}

References

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