Current RGB-D salient object detection (SOD) methods utilize the depth stream as
complementary information to the RGB stream. However, the depth maps are usually of low …

Existing RGB-D Salient Object Detection (SOD) methods take advantage of depth cues to
improve the detection accuracy, while pay insufficient attention to the quality of depth …

There are two main issues in RGB-D salient object detection:(1) how to effectively integrate
the complementarity from the cross-modal RGB-D data;(2) how to prevent the contamination …

Depth maps contain geometric clues for assisting Salient Object Detection (SOD). In this
paper, we propose a novel Cross-Modal Weighting (CMW) strategy to encourage …

RGB-D salient object detection (SOD) has been in the spotlight recently because it is an
important preprocessing operation for various vision tasks. However, despite advances in …

In this paper, we aim to develop an efficient and compact deep network for RGB-D salient
object detection, where the depth image provides complementary information to boost …

RGB-D salient object detection (SOD) aims to segment the most attractive objects in a pair of
cross-modal RGB and depth images. Currently, most existing RGB-D SOD methods focus on …

The popularity and promotion of depth maps have brought new vigor and vitality into salient
object detection (SOD), and a mass of RGB-D SOD algorithms have been proposed, mainly …

RGB-D based salient object detection (SOD) methods leverage the depth map as a valuable
complementary information for better SOD performance. Previous methods mainly resort to …

Existing state-of-the-art RGB-D salient object detection methods explore RGB-D data relying
on a two-stream architecture, in which an independent subnetwork is required to process …