Comprehensive Literature Survey on Deep Learning used in Image Memorability Prediction and Modification

Every day we are exposed to many images, only a few of which are remembered, while most of them we tend to forget. Though the human cognitive system has an enormous storage capacity [1,2], it may only be able to store some images as detailed as they are. Few images are remembered in great detail, even fewer in minor details, and the remainder is quickly forgotten [3]. Natural scenery photos, for example, are less likely to be remembered than images of animals, vehicles, and people [4]. According to previous research, images are consistently memorable to different viewers [5] and some images have better memorability than others. They also showed that memorability is an intrinsic and measurable property of an image. When we discuss memorability as a measurable property, the question of an artificial system successfully predicting the image memorability score comes along. Previous works done in the domain of image memorability can be grouped into three categories - understanding features that affect image memorability, Prediction of images' memorability scores, and modifying images' memorability.