Deep neural networks have shown their profound impact on achieving human-level
performance in visual saliency prediction. However, it is still unclear how they learn their …

Visual attention is one of the most significant characteristics for selecting and understanding
the outside redundancy world. The human vision system cannot process all information …

Visual attention analysis and prediction have long been important tasks in computer vision
and image processing. However, images often come along with various text descriptions in …

Fixation prediction aims to simulate human visual selection mechanism and estimate the
visual saliency degree of regions in a scene. In semantically rich scenes, there are generally …

Many visual attention models have been presented to obtain the saliency of a scene, ie, the
visually significant parts of a scene. However, some mechanisms are still not taken into …

Visual perception modelling of saliency detection has received widespread concerns
recently from both the cybernetics and computational intelligence domains. In particular …

Today, salient object detection has caught the interest of numerous researchers for a variety
of applications in computer vision. Most deep learning-based algorithms for SOD tasks …

Point cloud quality assessment (PCQA) has become an appealing research field in recent
days. Considering the importance of saliency detection in quality assessment, we propose …

Recently, deep learning has been widely employed across various domains. The
Convolution Neural Network (CNN), a popular deep learning algorithm, has been …

Underwater image detection remains a challenge due to problems such as noise,
illumination inhomogeneity and low contrast. To solve these problems, this paper proposes …