Many modern computer vision systems include several modules that perform different
processing operations packaged as a single pipeline architecture. This generally introduces …

Salient object detection is a critical task in the field of computer vision. However, existing
detection methods still face certain challenges, such as the inability to effectively integrate …

Previous RGB-D saliency detection methods adopt different fusion schemes to fuse the RGB
images and depth maps or their saliency maps. However, both the feature maps from …

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 …

Salient object detection, which simulates human visual perception in locating the most
significant object (s) in a scene, has been widely applied to various computer vision tasks …

This paper proposes an effective method to improve the saliency detection performance of
existing RGBD (RGB image with Depth map) saliency models. First, a progressive region …

This paper proposes a three-stage method using color, joint entropy and depth to detect
salient regions in an image. In the first stage, coarse saliency maps are computed through …

Recent years have witnessed growing interests in RGB-D Salient Object Detection (SOD),
benefiting from the ample spatial layout cues embedded in depth maps to help SOD models …

Despite significant progress, image saliency detection still remains a challenging task in
complex scenes and environments. Integrating multiple different but complementary cues …

With the advent of stereo camera saliency object detection for RGB-D image is attracting
more and more interest. Most existing algorithms treat RGB-D image as one RGB image and …