Progressive Guided Fusion Network with Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection

doi:10.1109/ACCESS.2021.3126338

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	Progressive Guided Fusion Network with Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection
	J. Wu; G. Han; H. Wang; H. Yang; Q. Li; D. Liu; F. Ye and P. Liu
刊名	IEEE Access
	2021
卷号	9 页码:150608-150622
ISSN号	21693536
DOI	10.1109/ACCESS.2021.3126338
英文摘要	The depth map contains abundant spatial structure cues, which makes it extensively introduced into saliency detection tasks for improving the detection accuracy. Nevertheless, the acquired depth map is often with uneven quality, due to the interference of depth sensors and external environments, posing a challenge when trying to minimize the disturbances from low-quality depth maps during the fusion process. In this article, to mitigate such issues and highlight the salient objects, we propose a progressive guided fusion network (PGFNet) with multi-modal and multi-scale attention for RGB-D salient object detection. Particularly, we first present a multi-modal and multi-scale attention fusion model (MMAFM) to fully mine and utilize the complementarity of features at different scales and modalities for achieving optimal fusion. Then, to strengthen the semantic expressiveness of the shallow-layer features, we design a multi-modal feature refinement mechanism (MFRM), which exploits the high-level fusion feature to guide the enhancement of the shallow-layer original RGB and depth features before they are fused. Moreover, a residual prediction module (RPM) is applied to further suppress background elements. Our entire network adopts a top-down strategy to progressively excavate and integrate valuable information. Compared with the state-of-the-art methods, experimental results demonstrate the effectiveness of our proposed method both qualitatively and quantitatively on eight challenging benchmark datasets. 2013 IEEE.
URL标识	查看原文
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/65557]
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	J. Wu,G. Han,H. Wang,et al. Progressive Guided Fusion Network with Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection[J]. IEEE Access,2021,9:150608-150622.
APA	J. Wu.,G. Han.,H. Wang.,H. Yang.,Q. Li.,...&F. Ye and P. Liu.(2021).Progressive Guided Fusion Network with Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection.IEEE Access,9,150608-150622.
MLA	J. Wu,et al."Progressive Guided Fusion Network with Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection".IEEE Access 9(2021):150608-150622.