基于堆叠边缘感知模块的显著性目标检测

doi:10.16451/j.cnki.issn1003-6059.202010005

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Abstract To improve the poor performance of the existing salient object detection algorithms in edge perception, a salient object detection algorithm based on stack edge-aware module is proposed to utilize high-level semantic information and low-level texture information effectively. Multi-scale backbone network is utilized as the backbone network to extract the multi-scale and multi-target salient features. In stacked edge-aware module, the high-level information and low-level information of the image are combined in an asymmetric manner to enhance the area of the salient object. The network outputs salient object detection results. The experiments on five public datasets indicate that the proposed algorithm produces better detection results and better performance in objective evaluation indicators and subjective visual effects.

Key words： Salient Object Detection(SOD) High-Level Semantic Information Low-Level Texture Information Edge-Aware Module

Received: 14 July 2020

ZTFLH:

TP391.4

Fund:National Natural Science Foundation of China(No.62076075)

Corresponding Authors: HU Xiao, Ph.D., professor. His research interests include computer vision, artificial intelligence and intelligent video analysis.

About author:: YANG Jiaxin, master student. His research interests include deep learning and salient object detection.XIANG Junjiang, master student. His research interests include video analysis and object detection.

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YANG Jiaxin,HU Xiao,XIANG Junjiang. Salient Object Detection Based on Stack Edge-Aware Module[J]. , 2020, 33(10): 906-916.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202010005 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2020/V33/I10/906

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