Alba G. Seco de Herrera
Rukiye Savran Kiziltepe
Jon Chamberlain
Mihai Gabriel Constantin
Claire-Hélène Demarty
Faiyaz Doctor
Bogdan Ionescu
Alan F. Smeaton
2021-06-21
<p>This paper describes the MediaEval 2020 Predicting Media Memorability task. After first being proposed at MediaEval 2018, the Predicting Media Memorability task is in its 3rd edition this year, as the prediction of short-term and long-term video memorability (VM) remains a challenging task. In 2020, the format remained the same as in previous editions. This year the videos are a subset of the TRECVid 2019 Video-to-Text dataset, containing more action rich video content as compared with the 2019 task. In this paper a description of some aspects of this task is provided, including its main characteristics, a description of the collection, the ground truth dataset, evaluation metrics and the requirements for participants’ run submissions.</p>
https://doi.org/10.5281/zenodo.5006058
oai:zenodo.org:5006058
eng
Zenodo
https://zenodo.org/communities/ai4media
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.5006057
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
MediaEval Multimedia Evaluation 2020, online, 14-15 December 2020
Media Memorability
Dataset
Benchmarking
Overview of MediaEval 2020 Predicting Media Memorability Task: What Makes a Video Memorable?
info:eu-repo/semantics/workingPaper