An Annotated Video Dataset for Computing Video Memorability

TL;DR

This paper introduces a comprehensive annotated video dataset with memorability scores, collected through an online memory game, to facilitate research on video memorability prediction.

Contribution

It provides a large-scale, annotated dataset with both short-term and long-term memorability measures, including reaction times and visual features, for short video clips.

Findings

Dataset used in MediaEval 2020 Video Memorability task

Includes annotations for short-term and long-term memorability

Provides visual features and captions for each video

Abstract

Using a collection of publicly available links to short form video clips of an average of 6 seconds duration each, 1,275 users manually annotated each video multiple times to indicate both long-term and short-term memorability of the videos. The annotations were gathered as part of an online memory game and measured a participant's ability to recall having seen the video previously when shown a collection of videos. The recognition tasks were performed on videos seen within the previous few minutes for short-term memorability and within the previous 24 to 72 hours for long-term memorability. Data includes the reaction times for each recognition of each video. Associated with each video are text descriptions (captions) as well as a collection of image-level features applied to 3 frames extracted from each video (start, middle and end). Video-level features are also provided. The dataset was used in the Video Memorability task as part of the MediaEval benchmark in 2020.