# Is Image Memorability Prediction Solved?

arXiv: https://arxiv.org/abs/1901.11420 · HTML: https://mlsanity.com/paper/1901.11420/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Jan 2019.

## Built on by (most cited first, 9 of 9)

- [Image Memorability Prediction with Vision Transformers](https://mlsanity.com/paper/2301.08647/) (2023)
- [Memorability: An image-computable measure of information utility](https://mlsanity.com/paper/2104.00805/) (2021)
- [What Images are More Memorable to Machines?](https://mlsanity.com/paper/2211.07625/) (2022)
- [Comprehensive Literature Survey on Deep Learning used in Image Memorability Prediction and Modification](https://mlsanity.com/paper/2301.06080/) (2022)
- [Feature representations useful for predicting image memorability](https://mlsanity.com/paper/2303.07679/) (2023)
- [Seeing Eye to AI: Comparing Human Gaze and Model Attention in Video Memorability](https://mlsanity.com/paper/2311.16484/) (2023)
- [Unforgettable Lessons from Forgettable Images: Intra-Class Memorability Matters in Computer Vision](https://mlsanity.com/paper/2412.20761/) (2024)
- [ADS: Approximate Densest Subgraph for Novel Image Discovery](https://mlsanity.com/paper/2402.08743/) (2024)
- [How to Take a Memorable Picture? Empowering Users with Actionable Feedback](https://mlsanity.com/paper/2602.21877/) (2026)

## Abstract (arXiv)

This paper deals with the prediction of the memorability of a given image. We start by proposing an algorithm that reaches human-level performance on the LaMem dataset - the only large scale benchmark for memorability prediction. The suggested algorithm is based on three observations we make regarding convolutional neural networks (CNNs) that affect memorability prediction. Having reached human-level performance we were humbled, and asked ourselves whether indeed we have resolved memorability prediction - and answered this question in the negative. We studied a few factors and made some recommendations that should be taken into account when designing the next benchmark.