Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 9
2854-2860

Sequential refined RGB-D saliency detection network based on channel weight

Bian Huajun
Wang Huajun
Zhao Hewei
School of Network Security, Chengdu University of Technology, Chengdu 610059, China
DOI: 10.19734/j.issn.1001-3695.2021.12.0696

Abstract

This paper proposed a new network framework for RGB-D salient object detection(SR-Net). In order to effectively integrate the complementarity of multi-model features, this paper took the depth feature extraction as an independent branch, used the convolutional block attention module(CBAM) to enhance the depth feature, and integrated the complementary information of the enhanced depth feature and RGB feature. Then, in order to remove feature redundancy and reduce the interfe-rence of background noise on the prediction results, it proposed a sequential refining network in the up-sampling network. That is, first, the primary global features were obtained by integrating the complementarity of multi-level and multi-scale features, and used the primary global feature weight matrix acquisition module(PFW) which based on the channel weight to obtain the weight matrix of the primary global feature, and then used the obtained weight matrix to refine the features of each level to suppress the interference which caused by background noise. Finally, in order to better optimize the whole network, it proposed a new loss function. The experimental results on four public datasets show that the model is superior to nine advanced methods in different model evaluation indexes, and achieves more advanced performance.

Foundation Support

四川省人工智能重点实验室项目(2020RYJ02)
模式识别与智能信息处理四川省高校重点实验室(MSSB-2020-10)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.12.0696
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 9
Section: Technology of Graphic & Image
Pages: 2854-2860
Serial Number: 1001-3695(2022)09-046-2854-07

Publish History

[2022-03-15] Accepted Paper
[2022-09-05] Printed Article

Cite This Article

卞华军, 王华军, 赵赫威. 基于通道权重的顺序精炼RGB-D显著检测网络 [J]. 计算机应用研究, 2022, 39 (9): 2854-2860. (Bian Huajun, Wang Huajun, Zhao Hewei. Sequential refined RGB-D saliency detection network based on channel weight [J]. Application Research of Computers, 2022, 39 (9): 2854-2860. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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