How Convolutional Neural Networks Remember Art

@article{Cetinic2018HowCN,
  title={How Convolutional Neural Networks Remember Art},
  author={Eva Cetinic and T. Lipic and S. Grgic},
  journal={2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP)},
  year={2018},
  pages={1-5}
}
  • Eva Cetinic, T. Lipic, S. Grgic
  • Published 2018
  • Computer Science
  • 2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP)
  • Inspired by the successful performance of Convolutional Neural Networks (CNN) in automatically predicting complex image properties such as memorability, in this work we explore their transferability to the domain of art images. We employ a CNN model trained to predict memorability scores of natural images to explore the memorability of artworks belonging to different genres and styles. Our experiments show that nude painting and portrait are the most memorable genres, while landscape and marine… CONTINUE READING

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