# Defining Image Memorability using the Visual Memory Schema

arXiv: https://arxiv.org/abs/1903.02056 · HTML: https://mlsanity.com/paper/1903.02056/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Mar 2019.

## Built on by (most cited first, 10 of 10)

- [Lifelong Teacher-Student Network Learning](https://mlsanity.com/paper/2107.04689/) (2021)
- [Image Memorability Prediction with Vision Transformers](https://mlsanity.com/paper/2301.08647/) (2023)
- [Long-Term Ad Memorability: Understanding & Generating Memorable Ads](https://mlsanity.com/paper/2309.00378/) (2023)
- [Memorability: An image-computable measure of information utility](https://mlsanity.com/paper/2104.00805/) (2021)
- [Unsupervised Local Discrimination for Medical Images](https://mlsanity.com/paper/2108.09440/) (2021)
- [Analysing the Memorability of a Procedural Crime-Drama TV Series, CSI](https://mlsanity.com/paper/2208.03479/) (2022)
- [Comprehensive Literature Survey on Deep Learning used in Image Memorability Prediction and Modification](https://mlsanity.com/paper/2301.06080/) (2022)
- [Unforgettable Lessons from Forgettable Images: Intra-Class Memorability Matters in Computer Vision](https://mlsanity.com/paper/2412.20761/) (2024)
- [Visual Sensation and Perception Computational Models for Deep Learning: State of the art, Challenges and Prospects](https://mlsanity.com/paper/2109.03391/) (2021)
- [ADS: Approximate Densest Subgraph for Novel Image Discovery](https://mlsanity.com/paper/2402.08743/) (2024)

## Abstract (arXiv)

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 organisation of image components human observers share when encoding and recognising 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.