A Computational Perspective on Visual Attention

By John K. Tsotsos. 2011

285 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

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In Computer Vision and Pattern Recognition

Citations in the corpus

Physiologically Inspired Model for the Visual Recognition of Transitive Hand Actions (2013, unknown): “Neural mechanisms supporting such computational functions have been extensively studied in the context of neural models for attention (Deco and Rolls, 2004; Hamker, 2006; Tsotsos, 2011).”
Coordinate Attention for Efficient Mobile Network Design (2021, background): “Attention mechanisms [41, 40] have been proven helpful in a variety of computer vision tasks, such as image classification [18, 17, 44, 1] and image segmentation [14, 19, 10].”
STNet: Selective Tuning of Convolutional Networks for Object Localization (2017, methodology): “The idea is using some form of facilitation or suppression, the visual representation is selected and modulated in a TD manner [27, 17].”
40 years of cognitive architectures: core cognitive abilities and practical applications (2018, methodology): “For more detailed explanations of the attentional mechanisms and review of the relevant psychological and neuroscience literature refer to Tsotsos (2011).”
Attentional Correlation Filter Network for Adaptive Visual Tracking (2017, methodology): “The importance of attentional mechanisms of the human visual system is highlighted by recent trends in neuroscience research [13,14,28], as well as by theoretical work on the computational aspects of visual attention [12, 34].”
Revisiting active perception (2016, background): “My solution is to seek a general purpose vision system that can be tuned to different functions depending on the task required of it and input it views (Tsotsos 2011).”