The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition

Jonathan Krause, Benjamin Sapp, Andrew Howard, Howard Zhou, Alexander Toshev, Tom Duerig, James Philbin, Li Fei-Fei. The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition. In Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling, editors, Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part III. Volume 9907 of Lecture Notes in Computer Science, pages 301-320, Springer, 2016. [doi]

@inproceedings{KrauseSHZTDPF16,
  title = {The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition},
  author = {Jonathan Krause and Benjamin Sapp and Andrew Howard and Howard Zhou and Alexander Toshev and Tom Duerig and James Philbin and Li Fei-Fei},
  year = {2016},
  doi = {10.1007/978-3-319-46487-9_19},
  url = {http://dx.doi.org/10.1007/978-3-319-46487-9_19},
  researchr = {https://researchr.org/publication/KrauseSHZTDPF16},
  cites = {0},
  citedby = {0},
  pages = {301-320},
  booktitle = {Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part III},
  editor = {Bastian Leibe and Jiri Matas and Nicu Sebe and Max Welling},
  volume = {9907},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-46486-2},
}