Most existing attention prediction research focuses on salient instances like humans and
objects. However the more complex interaction-oriented attention arising from the …

We propose to exploit the scanpath prediction technology to simulate human visual system
to automatically generate gaze scanpaths for VR/AR applications, to alleviate the equipment …

Most models of visual attention aim at predicting either top-down or bottom-up control as
studied using different visual search and free-viewing tasks. In this paper we propose the …

From a visual perception perspective, modern graphical user interfaces (GUIs) comprise a
complex graphics-rich two-dimensional visuospatial arrangement of text, images, and …

Understanding how attention varies across individuals has significant scientific and societal
impacts. However existing visual scanpath models treat attention uniformly neglecting …

Human attention modelling has proven, in recent years, to be particularly useful not only for
understanding the cognitive processes underlying visual exploration, but also for providing …

We introduce a new method called the Gaze Scanpath Transformer for predicting a search
target category during a visual search task. Previous methods for estimating visual search …

Progress in human behavior modeling involves understanding both implicit, early-stage
perceptual behavior such as human attention and explicit, later-stage behavior such as …

Reusable embeddings of user behaviour have shown significant performance
improvements for the personalised saliency prediction task. However, prior works require …

This paper introduces a novel system to enhance the spatiotemporal alignment of human
abilities in agent-based workflows. This optimization is realized through the application of …