Object-context inconsistencies affect gaze behavior differently than predicted by contextualized meaning maps
Marek A Pedziwiatr,
Thomas SA Wallis,
ConclusionHuman observers look more at objects that are semantically inconsistent with the scene context compared to consistent objects. Contextualized meaning maps do not show a similar sensitivity to this manipulation. In fact, on average, raw rating data–from which these maps are generated–indicate that humans rate inconsistent objects as slightly less meaningful.
My research interests include eye movements, saliency prediction, benchmarking, representation learning and statistics.
Professor for Computational Neuroscience and Machine Learning & Director of the Tübingen AI Center
Matthias Bethge is Professor for Computational Neuroscience and Machine Learning at the University of Tübingen and director of the Tübingen AI Center, a joint center between Tübingen University and MPI for Intelligent Systems that is part of the German AI strategy.