Global Guided Cross-Modal Cross-Scale Network for RGB-D Salient Object Detection

doi:10.3390/s23167221

CIOMP OpenIR

	Global Guided Cross-Modal Cross-Scale Network for RGB-D Salient Object Detection
	S. Wang, F. Jiang and B. Xu
	2023
发表期刊	Sensors
ISSN	14248220
卷号	23 期号:16
摘要	RGB-D saliency detection aims to accurately localize salient regions using the complementary information of a depth map. Global contexts carried by the deep layer are key to salient objection detection, but they are diluted when transferred to shallower layers. Besides, depth maps may contain misleading information due to the depth sensors. To tackle these issues, in this paper, we propose a new cross-modal cross-scale network for RGB-D salient object detection, where the global context information provides global guidance to boost performance in complex scenarios. First, we introduce a global guided cross-modal and cross-scale module named G2CMCSM to realize global guided cross-modal cross-scale fusion. Then, we employ feature refinement modules for progressive refinement in a coarse-to-fine manner. In addition, we adopt a hybrid loss function to supervise the training of G2CMCSNet over different scales. With all these modules working together, G2CMCSNet effectively enhances both salient object details and salient object localization. Extensive experiments on challenging benchmark datasets demonstrate that our G2CMCSNet outperforms existing state-of-the-art methods. © 2023 by the authors.
DOI	10.3390/s23167221
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收录类别	sci ; ei
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/67956
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	S. Wang, F. Jiang and B. Xu. Global Guided Cross-Modal Cross-Scale Network for RGB-D Salient Object Detection[J]. Sensors,2023,23(16).
APA	S. Wang, F. Jiang and B. Xu.(2023).Global Guided Cross-Modal Cross-Scale Network for RGB-D Salient Object Detection.Sensors,23(16).
MLA	S. Wang, F. Jiang and B. Xu."Global Guided Cross-Modal Cross-Scale Network for RGB-D Salient Object Detection".Sensors 23.16(2023).

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