Temporal salience considers how visual attention varies over time. Although visual salience
has been widely studied from a spatial perspective, its temporal dimension has been mostly ignored,
despite arguably being of utmost importance to understand the temporal evolution of attention
on dynamic contents. To address this gap, we proposed GLIMPSE, a novel measure to compute
temporal salience based on the observer-spatio-temporal consistency of raw gaze data. The measure
is conceptually simple, training free, and provides a semantically meaningful quantification of
visual attention over time. As an extension, we explored scoring algorithms to estimate temporal
salience from spatial salience maps predicted with existing computational models. However, these
approaches generally fall short when compared with our proposed gaze-based measure. GLIMPSE
could serve as the basis for several downstream tasks such as segmentation or summarization of
videos. GLIMPSE’s software and data are publicly available