---
title: "YFCC100M: The New Data in Multimedia Research (2015)"
description: "The core release is metadata only, distributed via Amazon AWS. 22 references, cited by 130 papers here."
authors: ["Bart Thomee", "David A. Shamma", "Gerald Friedland", "Benjamin Elizalde", "Karl Ni", "Douglas Poland", "Damian Borth", "Li-Jia Li"]
year: 2015
venue: "arXiv:1503.01817 · Communications of the ACM, 59(2), pp. 64-73, 2016"
source: "https://arxiv.org/abs/1503.01817"
doi: "10.1145/2812802"
arxiv: "1503.01817"
licence: "arXiv — non-exclusive license to distribute"
licence_url: "http://arxiv.org/licenses/nonexclusive-distrib/1.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/thomee-2015-yfcc100m-new-data-multimedia-research/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/thomee-2015-yfcc100m-new-data-multimedia-research/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2015](https://md.research.elamur.ai/free/en/papers/2015/) / YFCC100M: The New Data in Multimedia Research

# YFCC100M: The New Data in Multimedia Research

**Authors:** Bart Thomee, [David A. Shamma](https://md.research.elamur.ai/free/en/authors/david-a-shamma/), Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth and [Li-Jia Li](https://md.research.elamur.ai/free/en/authors/li-jia-li/) · **Year:** 2015 · **Venue:** [arXiv:1503.01817 · Communications of the ACM, 59(2), pp. 64-73, 2016](https://md.research.elamur.ai/free/en/venues/communications-of-the-acm/) ([Communications of the ACM 2015](https://md.research.elamur.ai/free/en/venues/communications-of-the-acm/2015/)) · **Publisher:** [Association for Computing Machinery](https://md.research.elamur.ai/free/en/publishers/association-for-computing-machinery/) · **Licence:** [arXiv — non-exclusive license to distribute](http://arxiv.org/licenses/nonexclusive-distrib/1.0/)

**Links:** [Publisher's page](https://doi.org/10.1145/2812802) · [PDF](https://arxiv.org/pdf/1503.01817) · [DOI 10.1145/2812802](https://doi.org/10.1145/2812802) · [arXiv 1503.01817](https://arxiv.org/abs/1503.01817) · [OpenAlex](https://openalex.org/W2250384498)

**Citations:** 1,541 citations (OpenAlex, 2026-10-14) · [130](https://md.research.elamur.ai/free/en/papers/thomee-2015-yfcc100m-new-data-multimedia-research/cited-by/) in our library, of the 149,439 papers whose bibliographies we read

## 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 Institute](https://md.research.elamur.ai/free/en/labs/international-computer-science-institute/) — Research institute, Berkeley, United States · 18 works · 16,608 citations
- [Yahoo](https://md.research.elamur.ai/free/en/companies/yahoo/) — Company, Sunnyvale, United States · 8 works · 11,973 citations
- [Lawrence Livermore National Laboratory](https://md.research.elamur.ai/free/en/labs/lawrence-livermore-national-laboratory/) — Research institute, Livermore, United States · 6 works · 2,127 citations

📚 Shelves (2): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 18,614 works · [👁️ Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-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.

```bibtex
@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}
}
```

- [← previous Document Modeling with Gated Recurrent Neural Network for Sentiment Classification](https://md.research.elamur.ai/free/en/papers/tang-2015-document-modeling-gated-recurrent-neural/)
- [next → SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation](https://md.research.elamur.ai/free/en/papers/hill-2015-simlex-999-evaluating-semantic-models/)
- [↑ back to papers of 2015](https://md.research.elamur.ai/free/en/papers/2015/)

## References

22 references, 2 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Bernd, J., Borth, D., Elizalde, B., Friedland, G., Gallagher, H., Gottlieb, L. R., Janin, A., Karabash-lieva, S., Takahashi, J., and Won, J. The YLI-MED corpus: Characteristics, procedures, and plans. CoRR abs/1503.04250 (2015). — [arXiv:1503.04250](https://arxiv.org/abs/1503.04250) [find](https://scholar.google.com/scholar?q=Bernd%2C+J%2E%2C+Borth%2C+D%2E%2C+Elizalde%2C+B%2E%2C+Friedland%2C+G%2E%2C+Gallagher%2C+H%2E%2C+Gottlieb%2C+L%2E+R%2E%2C+Janin%2C+A%2E%2C+Karabash%2Dlieva%2C+S%2E%2C+Takahashi%2C+J%2E%2C+and+Won%2C+J%2E+The+YLI%2DMED+corpus%3A+Characteristics%2C+procedures%2C+and+plans%2E)
2. Borgman, C. L. The conundrum of sharing research data. Journal of the American Society for Information Science and Technology 63, 6 (2012), 1059–1078. [find](https://scholar.google.com/scholar?q=Borgman%2C+C%2E+L%2E+The+conundrum+of+sharing+research+data%2E+Journal+of+the+American+Society+for+Information+Science+and+Technology+63%2C+6+%282012%29%2C+1059%E2%80%931078%2E)
3. Choi, J., Thomee, B., Friedland, G., Cao, L., Ni, K., Borth, D., Elizalde, B., Gottlieb, L., Carrano, C., Pearce, R., and Poland, D. The placing task: A large-scale geo-estimation challenge for social-media videos and images. In Proceedings of the ACM International Workshop on Geotagging and Its App… [find](https://scholar.google.com/scholar?q=Choi%2C+J%2E%2C+Thomee%2C+B%2E%2C+Friedland%2C+G%2E%2C+Cao%2C+L%2E%2C+Ni%2C+K%2E%2C+Borth%2C+D%2E%2C+Elizalde%2C+B%2E%2C+Gottlieb%2C+L%2E%2C+Carrano%2C+C%2E%2C+Pearce%2C+R%2E%2C+and+Poland%2C+D%2E+The+placing+task%3A+A+large%2Dscale+geo%2Destimation+challenge+for+social)
4. Crandall, D. J., Backstrom, L., Huttenlocher, D., and Kleinberg, J. Mapping the world’s photos. In Proceedings of the IW3C2 International Conference on World Wide Web (2009), pp. 761–770. [find](https://scholar.google.com/scholar?q=Crandall%2C+D%2E+J%2E%2C+Backstrom%2C+L%2E%2C+Huttenlocher%2C+D%2E%2C+and+Kleinberg%2C+J%2E+Mapping+the+world%E2%80%99s+photos%2E+In+Proceedings+of+the+IW3C2+International+Conference+on+World+Wide+Web+%282009%29%2C+pp%2E+761%E2%80%93770%2E)
5. Deng, J., Dong, W., Socher, R., Li, L., Li, K., and Fei-Fei, L. ImageNet: A large-scale hierarchical image database. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2009), pp. 248–255. [find](https://scholar.google.com/scholar?q=Deng%2C+J%2E%2C+Dong%2C+W%2E%2C+Socher%2C+R%2E%2C+Li%2C+L%2E%2C+Li%2C+K%2E%2C+and+Fei%2DFei%2C+L%2E+ImageNet%3A+A+large%2Dscale+hierarchical+image+database%2E+In+Proceedings+of+the+IEEE+Conference+on+Computer+Vision+and+Pattern+Recognition+%282)
6. Facebook, Ericsson, and Qualcomm. A focus on efficiency. Tech. rep., Facebook Inc., 2013. [find](https://scholar.google.com/scholar?q=Facebook%2C+Ericsson%2C+and+Qualcomm%2E+A+focus+on+efficiency%2E+Tech%2E+rep%2E%2C+Facebook+Inc%2E%2C+2013%2E)
7. Fienberg, S. E., Martin, M. E., Straf, M. L., et al. Sharing research data. National Academy Press, 1985. [find](https://scholar.google.com/scholar?q=Fienberg%2C+S%2E+E%2E%2C+Martin%2C+M%2E+E%2E%2C+Straf%2C+M%2E+L%2E%2C+et+al%2E+Sharing+research+data%2E+National+Academy+Press%2C+1985%2E)
8. Good, J. How many photos have ever been taken? [https://web.archive.org/web/20150203215607/http://blog.1000memories.com/94-number-of-photos-ever-taken-digital-and-analog-in-shoebox](https://web.archive.org/web/20150203215607/http://blog.1000memories.com/94-number-of-photos-ever-taken-digital-and-analog-in-shoebox), September 2011. Accessed July, 2015. [↗](https://web.archive.org/web/20150203215607/http://blog.1000memories.com/94-number-of-photos-ever-taken-digital-and-analog-in-shoebox)
9. Hays, J., and Efros, A. A. IM2GPS: estimating geographic information from a single image. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2008). [find](https://scholar.google.com/scholar?q=Hays%2C+J%2E%2C+and+Efros%2C+A%2E+A%2E+IM2GPS%3A+estimating+geographic+information+from+a+single+image%2E+In+Proceedings+of+the+IEEE+Conference+on+Computer+Vision+and+Pattern+Recognition+%282008%29%2E)
10. Hecht, B., Hong, L., Suh, B., and Chi, E. H. Tweets from Justin Bieber’s heart: the dynamics of the location field in user profiles. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2011), pp. 237–246. [find](https://scholar.google.com/scholar?q=Hecht%2C+B%2E%2C+Hong%2C+L%2E%2C+Suh%2C+B%2E%2C+and+Chi%2C+E%2E+H%2E+Tweets+from+Justin+Bieber%E2%80%99s+heart%3A+the+dynamics+of+the+location+field+in+user+profiles%2E+In+Proceedings+of+the+SIGCHI+Conference+on+Human+Factors+in+Computi)
11. Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R. B., Guadarrama, S., and Darrell, T. [Caffe: convolutional architecture for fast feature embedding](https://md.research.elamur.ai/free/en/papers/jia-2014-caffe-convolutional-architecture-fast-feature/). In ACM Multimedia (2014), pp. 675–678.
12. Kremerskothen, K. Welcome the internet archive to the commons. [https://blog.flickr.net/2014/08/29/welcome-the-internet-archive-to-the-commons/](https://blog.flickr.net/2014/08/29/welcome-the-internet-archive-to-the-commons/), August 2014. Accessed July, 2015. [↗](https://blog.flickr.net/2014/08/29/welcome-the-internet-archive-to-the-commons/)
13. Krizhevsky, A., Sutskever, I., and Hinton, G. E. [ImageNet classification with deep convolutional neural networks](https://md.research.elamur.ai/free/en/papers/krizhevsky-2012-imagenet-classification-deep-convolutional/). In Advances in Neural Information Processing Systems (2012), pp. 1097–1105.
14. Li, L., Socher, R., and Fei-Fei, L. Towards total scene understanding: classification, annotation and segmentation in an automatic framework. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2009), pp. 2036–2043. [find](https://scholar.google.com/scholar?q=Li%2C+L%2E%2C+Socher%2C+R%2E%2C+and+Fei%2DFei%2C+L%2E+Towards+total+scene+understanding%3A+classification%2C+annotation+and+segmentation+in+an+automatic+framework%2E+In+Proceedings+of+the+IEEE+Conference+on+Computer+Vision+a)
15. Rattenbury, T., Good, N., and Naaman, M. Towards automatic extraction of event and place semantics from Flickr tags. In Proceedings of the ACM International Conference on Research and Development in Information Retrieval (2007), pp. 103–110. [find](https://scholar.google.com/scholar?q=Rattenbury%2C+T%2E%2C+Good%2C+N%2E%2C+and+Naaman%2C+M%2E+Towards+automatic+extraction+of+event+and+place+semantics+from+Flickr+tags%2E+In+Proceedings+of+the+ACM+International+Conference+on+Research+and+Development+in+I)
16. Renear, A. H., Sacchi, S., and Wickett, K. M. Definitions of dataset in the scientific and technical literature. In Proceedings of the Annual Meeting of the American Society for Information Science and Technology (2010), pp. 1–4. [find](https://scholar.google.com/scholar?q=Renear%2C+A%2E+H%2E%2C+Sacchi%2C+S%2E%2C+and+Wickett%2C+K%2E+M%2E+Definitions+of+dataset+in+the+scientific+and+technical+literature%2E+In+Proceedings+of+the+Annual+Meeting+of+the+American+Society+for+Information+Science+an)
17. Snavely, N., Seitz, S., and Szeliski, R. Photo tourism: exploring photo collections in 3D. ACM Transactions on Graphics 25, 3 (2006), 835–846. [find](https://scholar.google.com/scholar?q=Snavely%2C+N%2E%2C+Seitz%2C+S%2E%2C+and+Szeliski%2C+R%2E+Photo+tourism%3A+exploring+photo+collections+in+3D%2E+ACM+Transactions+on+Graphics+25%2C+3+%282006%29%2C+835%E2%80%93846%2E)
18. Swan, A., and Brown, S. To share or not to share: publication and quality assurance of research data outputs. Tech. rep., Research Information Network, 2008. [find](https://scholar.google.com/scholar?q=Swan%2C+A%2E%2C+and+Brown%2C+S%2E+To+share+or+not+to+share%3A+publication+and+quality+assurance+of+research+data+outputs%2E+Tech%2E+rep%2E%2C+Research+Information+Network%2C+2008%2E)
19. Van Dijck, J. Digital photography: communication, identity, memory. Visual Communication 7, 1 (2008), 57–76. [find](https://scholar.google.com/scholar?q=Van+Dijck%2C+J%2E+Digital+photography%3A+communication%2C+identity%2C+memory%2E+Visual+Communication+7%2C+1+%282008%29%2C+57%E2%80%9376%2E)
20. Wilson, M. L., Chi, E. H., Reeves, S., and Coyle, D. RepliCHI: The Workshop II. In Proceedings of the International Conference on Human Factors in Computing Systems, Extended Abstracts (2014), pp. 33–36. [find](https://scholar.google.com/scholar?q=Wilson%2C+M%2E+L%2E%2C+Chi%2C+E%2E+H%2E%2C+Reeves%2C+S%2E%2C+and+Coyle%2C+D%2E+RepliCHI%3A+The+Workshop+II%2E+In+Proceedings+of+the+International+Conference+on+Human+Factors+in+Computing+Systems%2C+Extended+Abstracts+%282014%29%2C+pp%2E+33%E2%80%93)
21. Yelp dataset challenge. [http://yelp.com/dataset_challenge/](http://yelp.com/dataset_challenge/). Accessed July, 2015. [↗](http://yelp.com/dataset_challenge/)
22. Youtube press statistics. [http://youtube.com/yt/press/statistics.html](http://youtube.com/yt/press/statistics.html). Accessed July, 2015. [↗](http://youtube.com/yt/press/statistics.html)

*Updated 2 November 2026*