RGB-D salient object detection (SOD) usually describes two modes' classification or
regression problem, namely RGB and depth. The existing RGB-D SOD methods use depth …

Traditional image editing techniques cannot be directly used to process stereoscopic media,
as extra constraints are required to ensure consistent changes between the left and right …

With the emerging development of three-dimensional (3D) related technologies, 3D visual
saliency modeling is becoming particularly important and challenging. This paper presents a …

Visual attention is an important mechanism in the human visual system (HVS) and there
have been numerous saliency detection algorithms designed for 2D images/video recently …

This work presents a novel cross-modality method for acquiring human visual perception on
stereoscopic image quality ranking (SIQR), aiming to learn latent biological representations …

In recent years, there has been great progress in the wider use of three-dimensional (3D)
technologies. With increasing sources of 3D content, a useful tool is needed to evaluate the …

Automatic detection of salient objects in images attracts much research attention for its
usage in numerous multimedia applications. In this paper, we propose a saliency fusion and …

Significant improvement has been achieved lately in color and depth data based salient
object detection on images from varied datasets, which is mainly due to RGB-D fusion using …

Many convolutional neural network (CNN)-based approaches for stereoscopic salient object
detection involve fusing either low-level or high-level features from the color and disparity …

Least squares regression (LSR) is widely used for pattern classification. Some variants
based on it try to enlarge the margin between different classes to achieve better …