Neurobiology of Attention

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Global-and-local attention networks for visual recognition (2018, background): “While biology is sometimes mentioned as a source of inspiration [1–7], the attentional mechanisms that have been considered by the computer vision community remain limited in comparison to the richness and diversity of the processes used by our visual system (see [8] for a review).”
Reinforcement Learning for Visual Object Detection (2016, background): “In contrast, biological systems have a pattern of search that can be characterized as 'saccade and fixate'[17], where a small set of scene locations are investigated sequentially, in order to accumulate sufficient evidence on the target location .”
Dynamic Eye Movement Datasets and Learnt Saliency Models for Visual Action Recognition (2012, background): “The problem of visual attention and the prediction of visual saliency have long been of interest in the human vision community[16, 10, 18].”
Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images (2014, background): “tense research both in neuroscience [15] and in computer vision, where saliency-based preprocessing has found a wide applicability from image/video compression and quality assessment to object and action recognition.”