Given the widespread adoption of depth-sensing acquisition devices, RGB-D videos and
related data/media have gained considerable traction in various aspects of daily life …

Salient object detection (SOD) aims to identify standout elements in a scene, with recent
advancements primarily focused on integrating depth data (RGB-D) or temporal data from …

With the rapid development of depth sensor, more and more RGB-D videos could be
obtained. Identifying the foreground in RGB-D videos is a fundamental and important task …

Exploiting long-range semantic contexts and geometric information is crucial to infer salient
objects from RGB and depth features. However, existing methods mainly focus on …

Recently CNN-based RGB-D salient object detection (SOD) has obtained significant
improvement on detection accuracy. However, existing models often fail to perform well in …

Recently proposed state-of-the-art saliency detection models rely heavily on labeled
datasets and rarely focus on perfect RGBD feature fusion, which lowers their generalization …

Depth can provide useful geographical cues for salient object detection (SOD), and has
been proven helpful in recent RGB-D SOD methods. However, existing video salient object …

Complex backgrounds and similar appearances between objects and their surroundings are
generally recognized as challenging scenarios in Salient Object Detection (SOD). This …

Compared with RGB salient object detection (SOD) methods, RGB-D SOD models show
better performance in many challenging scenarios by leveraging spatial information …

The use of RGB-D information for salient object detection (SOD) has been extensively
explored in recent years. However, relatively few efforts have been put toward modeling …