Research in psychology has shown that when people are told not to think about a pink elephant they cannot avoid doing just that. Similar results are found for language production in that people leak information about hidden figures when instructed to ignore those figures. It is argued that the salience of information plays a crucial role in these effects. The present study investigates how diff...

As a component of low-level vision processing, saliency detection facilitates subsequent processing such as object detection or recognition. In this paper, we argue that a reasonable saliency detector should have the ability to: (1) Detect both small and large saliency regions. The size of salient regions vary greatly. When the salient region is large, however, because center-surround algorithm...

Attention is attracted exogenously by physically salient stimuli, but this effect can be dampened by endogenous attention settings, a phenomenon called "contingent capture." Emotionally salient stimuli are also thought to exert a strong exogenous influence on attention, especially in anxious individuals, but whether and how top-down attention can ameliorate bottom-up capture by affective stimul...

Human eyes can identify person identities based on small salient regions, i.e. person saliency is distinctive and reliable. Saliency relates to matching regions with attributes that make a person distinctive and are useful in finding the same person across camera views. Person re-identification with saliency learning can be applied in human tracking, surveillance , retrieval etc.

Visual saliency computation is about detecting and understanding salient regions and elements in a visual scene. Algorithms for visual saliency computation can give clues to where people will look in images, what objects are visually prominent in a scene, etc. Such algorithms could be useful in a wide range of applications in computer vision and graphics. In this thesis, we study the following ...

Purpose – This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and information acquisition technologies, more complex objects appear in high-resolution remote sensing images. Traditional visual features are no longer precise enough to describe the images. Design/methodology/approach – A novel...

This paper presents a co-salient object detection method to find common salient regions in a set of images. We utilize deep saliency networks to transfer co-saliency prior knowledge and better capture high-level semantic information, and the resulting initial co-saliency maps are enhanced by seed propagation steps over an integrated graph. The deep saliency networks are trained in a supervised ...

Recent work in the computational modeling of visual attention has demonstrated that a purely bottom-up approach to identifying salient regions within an image can be successfully applied to diverse and practical problems from target recognition to the placement of advertisement. This paper proposes an application of a combination of computational models of visual attention to the image retrieva...

Stimulus-driven attention can improve working memory (WM) when drawn to behaviorally relevant information, but the neural mechanisms underlying this effect are unclear. The present study used functional magnetic resonance imaging (fMRI) to test competing hypotheses regarding the nature of the benefits of stimulus-driven attention to WM: that stimulus-driven attention benefits WM directly via sa...