# Experiences from the MediaEval Predicting Media Memorability Task

arXiv: https://arxiv.org/abs/2212.03955 · HTML: https://mlsanity.com/paper/2212.03955/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 16 references that are in the map.
- First posted on arXiv 7 Dec 2022.

## Builds on (most cited first, 8 of 8)

- [VideoMem: Constructing, Analyzing, Predicting Short-term and Long-term Video Memorability](https://mlsanity.com/paper/1812.01973/) (2018)
- [Multimodal Memorability: Modeling Effects of Semantics and Decay on Video Memorability](https://mlsanity.com/paper/2009.02568/) (2020)
- [TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval](https://mlsanity.com/paper/2009.09984/) (2020)
- [Overview of MediaEval 2020 Predicting Media Memorability Task: What Makes a Video Memorable?](https://mlsanity.com/paper/2012.15650/) (2020)
- [An Annotated Video Dataset for Computing Video Memorability](https://mlsanity.com/paper/2112.02303/) (2021)
- [Overview of The MediaEval 2021 Predicting Media Memorability Task](https://mlsanity.com/paper/2112.05982/) (2021)
- [Predicting Media Memorability: Comparing Visual, Textual and Auditory Features](https://mlsanity.com/paper/2112.07969/) (2021)
- [Overview of the EEG Pilot Subtask at MediaEval 2021: Predicting Media Memorability](https://mlsanity.com/paper/2201.00620/) (2021)

## Built on by (most cited first, 2 of 2)

- [Introducing MeMo: A Multimodal Dataset for Memory Modelling in Multiparty Conversations](https://mlsanity.com/paper/2409.13715/) (2024)
- [The Emotion-Memory Link: Do Memorability Annotations Matter for Intelligent Systems?](https://mlsanity.com/paper/2507.14084/) (2025)

## Abstract (arXiv)

The Predicting Media Memorability task in the MediaEval evaluation campaign has been running annually since 2018 and several different tasks and data sets have been used in this time. This has allowed us to compare the performance of many memorability prediction techniques on the same data and in a reproducible way and to refine and improve on those techniques. The resources created to compute media memorability are now being used by researchers well beyond the actual evaluation campaign. In this paper we present a summary of the task, including the collective lessons we have learned for the research community.