Data Limitations for Modeling Top-Down Effects on Drivers' Attention

arXiv:2404.08749v1 Announce Type: new
Abstract: Driving is a visuomotor task, i.e., there is a connection between what drivers see and what they do. While some models of drivers' gaze account for top-down effects of drivers' actions, the majority learn only bottom-up correlations between human gaze and driving footage. The crux of the problem is lack of public data with annotations that could be used to train top-down models and evaluate how well models of any kind capture effects of task …

abstract arxiv attention correlations crux cs.cv data drivers driving effects human learn limitations modeling type