Defining Image Memorability using the Visual Memory Schema

Research output: Contribution to journalArticlepeer-review


Memorability of an image is a characteristic determined by the human observers’ ability to remember images they have seen. Yet recent work on image memorability defines it as an intrinsic property that can be obtained independent of the observer. The current study aims to enhance our understanding and prediction of image memorability, improving upon existing approaches by incorporating the properties of cumulative human annotations. We propose a new concept called the Visual Memory Schema (VMS) referring to an organization of image components human observers share when encoding and recognizing images. The concept of VMS is operationalised by asking human observers to define memorable regions of images they were asked to remember during an episodic memory test. We then statistically assess the consistency of VMSs across observers for either correctly or incorrectly recognised images. The associations of the VMSs with eye fixations and saliency are analysed separately as well. Lastly, we adapt various deep learning architectures for the reconstruction and prediction of memorable regions in images and analyse the results when using transfer learning at the outputs of different convolutional network layers.
Original languageEnglish
Pages (from-to)2165-2178
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number9
Early online date2 May 2019
Publication statusPublished - 1 Sept 2020


  • cs.CV

Cite this