Five important trends have emerged from recent work on computational models of focal
visual attention that emphasize the bottom-up, image-based control of attentional …

Distractor suppression refers to the ability to filter out distracting and task-irrelevant
information. Distractor suppression is essential for survival and considered a key aspect of …

Person Re-identification (re-id) aims to match people across non-overlapping camera views
in a public space. It is a challenging problem because many people captured in surveillance …

Selective visual attention is believed to be responsible for serializing visual information for
recognizing one object at a time in a complex scene. But how can we attend to objects …

We evaluate the applicability of a biologically-motivated algorithm to select visually-salient
regions of interest in video streams for multiply-foveated video compression. Regions are …

Based on concepts of the human visual system, computational visual attention systems aim
to detect regions of interest in images. Psychologists, neurobiologists, and computer …

A key problem in learning multiple objects from unlabeled images is that it is a priori
impossible to tell which part of the image corresponds to each individual object, and which …

Most previous studies on visual saliency have only focused on static or dynamic 2D scenes.
Since the human visual system has evolved predominantly in natural three dimensional …

We propose a computational model for the task-specific guidance of visual attention in real-
world scenes. Our model emphasizes four aspects that are important in biological vision …

Integration of goal-driven, top-down attention and image-driven, bottom-up attention is
crucial for visual search. Yet, previous research has mostly focused on models that are …