KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment

Vlad Hosu, Hanhe Lin, Tamás Szirányi, Dietmar Saupe. KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment. IEEE Transactions on Image Processing, 29:4041-4056, 2020. [doi]

@article{HosuLSS20,
  title = {KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment},
  author = {Vlad Hosu and Hanhe Lin and Tamás Szirányi and Dietmar Saupe},
  year = {2020},
  doi = {10.1109/TIP.2020.2967829},
  url = {https://doi.org/10.1109/TIP.2020.2967829},
  researchr = {https://researchr.org/publication/HosuLSS20},
  cites = {0},
  citedby = {0},
  journal = {IEEE Transactions on Image Processing},
  volume = {29},
  pages = {4041-4056},
}