@article{TEXTUAL,
      recid = {6631},
      author = {Davis, Trent M. and Bainbridge, Wilma A.},
      title = {Memory for artwork is predictable},
      journal = {PNAS},
      address = {2023-07-03},
      number = {TEXTUAL},
      abstract = {Viewing art is often seen as a highly personal and  subjective experience. However, are there universal factors  that make a work of art memorable? We conducted three  experiments, where we recorded online memory performance  for 4,021 paintings from the Art Institute of Chicago,  tested in-person memory after an unconstrained visit to the  Art Institute, and obtained abstract attribute measures  such as beauty and emotional valence for these pieces.  Participants showed significant agreement in their memories  both online and in-person, suggesting that pieces have an  intrinsic "memorability" based solely on their visual  properties that is predictive of memory in a naturalistic  museum setting. Importantly, ResMem, a deep learning neural  network designed to estimate image memorability, could  significantly predict memory both online and in-person  based on the images alone, and these predictions could not  be explained by other low- or high-level attributes like  color, content type, aesthetics, and emotion. A regression  comprising ResMem and other stimulus factors could predict  as much as half of the variance of in-person memory  performance. Further, ResMem could predict the fame of a  piece, despite having no cultural or historical knowledge.  These results suggest that perceptual features of a  painting play a major role in influencing its success, both  in memory for a museum visit and in cultural memory over  generations. },
      url = {http://knowledge.uchicago.edu/record/6631},
}