The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
YFCC100M: the new data in multimedia research
Open accessAbstract
This publicly available curated dataset of almost 100 million photos and videos is free and legal for all.
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Citations
Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
ImageNet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333
Self-citationCaffe: Convolutional Architecture for Fast Feature Embedding
Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., & Darrell, T. (2014) · Proceedings of the 22nd ACM international conference on Multimedia · doi:10.1145/2647868.2654889 · Cited by 11,077
Caffe: Convolutional Architecture for Fast Feature Embedding
Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., & Darrell, T. J. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1408.5093 · Cited by 3,752
Photo tourism: exploring photo collections in 3D
Snavely, N., Seitz, S. M., & Szeliski, R. (2006) · ACM Transactions on Graphics · doi:10.1145/1141911.1141964 · Cited by 2,866
ImageNet: A large-scale hierarchical image database
Deng, J. H., Dong, W. F., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvprw.2009.5206848 · Cited by 2,714
Self-citationThe conundrum of sharing research data
Borgman, C. L. (2012) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22634 · Cited by 880
IM2GPS: estimating geographic information from a single image
Hays, J., & Efros, A. A. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587784 · Cited by 877
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van Dijck, J. (2008) · Visual Communication · doi:10.1177/1470357207084865 · Cited by 508
Research works printed but not linked: 7
- Deng J., 2009, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Miami, FL, June 20--25)
- Good J., Internet Archive Wayback Machine
- Hays J., 2008, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Anchorage, AK, June 23--28)
- Kremerskothen K., 2014, Flickr
- Krizhevsky A., 2012, NY, 1097, 1105
- Li L., 2009, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Miami, FL, June 20--25)
- 10.5555/1920331.1920447 · doi:10.5555/1920331.1920447
Cited by
YOLO9000: Better, Faster, Stronger
Redmon, J., & Farhadi, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.690 · Cited by 19,892
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Howard, A. G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., & Adam, H. (2017) · arXiv · doi:10.48550/arxiv.1704.04861 · Cited by 19,015
Learning Transferable Visual Models From Natural Language Supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al. (2021) · arXiv · doi:10.48550/arxiv.2103.00020 · Cited by 15,293
Momentum Contrast for Unsupervised Visual Representation Learning
He, K., Fan, H., Wu, Y., Xie, S., & Girshick, R. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00975 · Cited by 13,347
Emerging Properties in Self-Supervised Vision Transformers
Caron, M., Touvron, H., Misra, I., Jegou, H., Mairal, J., Bojanowski, P., & Joulin, A. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00951 · Cited by 5,638
Metadata
- Authors
- Thomee, B., Shamma, D. A., Friedland, G., Elizalde, B., Ni, K., Poland, D., Borth, D., & Li, L.-J.
- Venue
- Communications of the ACM
- Published
- 2016-01-25
- Volume
- 59
- Issue
- 2
- Pages
- 64-73
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2250384498
- Cited by
- 1,541
- References
- 18
- FWCI
- 99.03
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- CoChat. (2026). Citation check: YFCC100M: the new data in multimedia research. https://app.cochat.ai/papers/10.1145/2812802
- The paper
- Thomee, B., Shamma, D. A., Friedland, G., Elizalde, B., Ni, K., Poland, D., Borth, D., & Li, L.-J. (2016). YFCC100M: the new data in multimedia research. Communications of the ACM. https://doi.org/10.1145/2812802
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
