Trends, Applications, and Challenges in Human Attention Modelling
Abstract
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.
Cite
@article{arxiv.2402.18673,
title = {Trends, Applications, and Challenges in Human Attention Modelling},
author = {Giuseppe Cartella and Marcella Cornia and Vittorio Cuculo and Alessandro D'Amelio and Dario Zanca and Giuseppe Boccignone and Rita Cucchiara},
journal= {arXiv preprint arXiv:2402.18673},
year = {2024}
}
Comments
Accepted at IJCAI 2024 Survey Track