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.
Cite
@article{arxiv.2212.03955,
title = {Experiences from the MediaEval Predicting Media Memorability Task},
author = {Alba García Deco de Herrera and Mihai Gabriel Constantin and Chaire-Hélène Demarty and Camilo Fosco and Sebastian Halder and Graham Healy and Bogdan Ionescu and Ana Matran-Fernandez and Alan F. Smeaton and Mushfika Sultana and Lorin Sweeney},
journal= {arXiv preprint arXiv:2212.03955},
year = {2022}
}
Comments
7 pages, 2 figures, 1 table. Presented at the NeurIPS 2022 Workshop on Memory in Artificial and Real Intelligence (MemARI), 2 December 2022, New Orleans, USA