Video saliency detection (VSD) aims at fast locating the most attractive
objects/things/patterns in a given video clip. Existing VSD-related works have mainly relied …

Audio information has been bypassed by most of current visual attention prediction studies.
However, sound could have influence on visual attention and such influence has been …

Conversation scenes are a typical example in which classical models of visual attention
dramatically fail to predict eye positions. Indeed, these models rarely consider faces as …

In this article, we propose to predict human eye fixation through incorporating both audio
and visual cues. Traditional visual attention models generally make the utmost of stimuli's …

Visual and audio events simultaneously occur and both attract attention. However, most
existing saliency prediction works ignore the influence of audio and only consider vision …

Over the past few years, deep neural networks (DNNs) have exhibited great success in
predicting the saliency of images. However, there are few works that apply DNNs to predict …

The understanding of the mechanisms behind focus of attention in a visual scene is a
problem of great interest in visual perception and computer vision. In this paper, we describe …

Recently, video streams have occupied a large proportion of Internet traffic, most of which
contain human faces. Hence, it is necessary to predict saliency on multiple-face videos …

With the booming development of smart devices, mobile videos have drawn broad interest
when humans surf social media. Different from traditional long-form videos, mobile videos …

Classical visual attention models neither consider social cues, such as faces, nor auditory
cues, such as speech. However, faces are known to capture visual attention more than any …