Attention is the important ability to flexibly control limited computational resources. It has
been studied in conjunction with many other topics in neuroscience and psychology …

We summarize the various strands of research on peripheral vision and relate them to
theories of form perception. After a historical overview, we describe quantifications of the …

In this paper, we aim to predict human eye fixation with view-free scenes based on an end-to-
end deep learning architecture. Although convolutional neural networks (CNNs) have made …

Saliency in Context (SALICON) is an ongoing effort that aims at understanding and
predicting visual attention. This paper presents a new method to collect large-scale human …

How best to evaluate a saliency model's ability to predict where humans look in images is an
open research question. The choice of evaluation metric depends on how saliency is …

Perceptual image quality assessment (IQA) aims to use computational models to measure
the image quality in consistent with subjective evaluations. Visual saliency (VS) has been …

We offer a formal treatment of choice behavior based on the premise that agents minimize
the expected free energy of future outcomes. Crucially, the negative free energy or quality of …

Understanding where people look in images is an important problem in computer vision.
Despite significant research, it remains unclear to what extent human fixations can be …

Previous research in visual saliency has been focused on two major types of models namely
fixation prediction and salient object detection. The relationship between the two, however …

Automatic estimation of salient object regions across images, without any prior assumption
or knowledge of the contents of the corresponding scenes, enhances many computer vision …