Trends, Applications, and Challenges in Human Attention Modelling
Giuseppe Cartella Marcella Cornia Vittorio Cuculo Alessandro D'Amelio Dario Zanca Giuseppe Boccignone Rita Cucchiara
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 support to artificial intelligence models
that aim to solve problems in various domains, including image and video
processing, vision-and-language applications, and language modelling. This
survey offers a reasoned overview of recent efforts to integrate human
attention mechanisms into contemporary deep learning models and discusses
future research directions and challenges. For a comprehensive overview on the
ongoing research refer to our dedicated repository available at
https://github.com/aimagelab/awesome-human-visual-attention.