Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

When dealing with objects with complex structures, saliency detection confronts a critical
problem namely that detection accuracy could be adversely affected if salient foreground or …

Although depth information plays an important role in the human vision system, it is not yet
well-explored in existing visual saliency computational models. In this work, we first …

Numerous efforts have been made to design various low-level saliency cues for RGBD
saliency detection, such as color and depth contrast features as well as background and …

Complex structures commonly exist in natural images. When an image contains small-scale
high-contrast patterns either in the background or foreground, saliency detection could be …

Most previous works on saliency detection are dedicated to 2D images. Recently it has been
shown that 3D visual information supplies a powerful cue for saliency analysis. In this paper …

Existing advanced saliency systems have been proposed using Convolutional Neural
Networks (CNNs), the prior knowledge of objectness is crucial for saliency detection …

Recently still image-based human action recognition has become an active research topic in
computer vision and pattern recognition. It focuses on identifying a person׳ s action or …

There is more to images than their objective physical content: for example, advertisements
are created to persuade a viewer to take a certain action. We propose the novel problem of …

In this paper, we present a novel attention-modulated visual tracking algorithm that
decomposes an object into multiple cognitive units, and trains multiple elementary trackers …