Overview of MediaEval 2020 Predicting Media Memorability Task: What Makes a Video Memorable?
This task addresses the challenging problem of predicting video memorability for researchers and participants in the MediaEval benchmark.
This paper describes the MediaEval 2020 Predicting Media Memorability task, which aims to predict short-term and long-term video memorability. It details the task's characteristics, the dataset (a subset of TRECVid 2019 Video-to-Text), ground truth, evaluation metrics, and submission requirements for participants.
This paper describes the MediaEval 2020 \textit{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.