Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 2
601-605

Supervised significant detection based on image level labels and superpixel blocks

Tan Taizhe1,2
Xuan Kangxi1
Zeng Qunsheng1
1. College of Computer, Guangdong University of Technology, Guangzhou 510006, China
2. Heyuan Guanggong Collaborative Innovation Research Institute, Heyuan Guangdong 517000, China
DOI: 10.19734/j.issn.1001-3695.2018.06.0576

Abstract

Aiming at the high cost of obtaining the training data set, this paper proposed a new weak supervision method for image saliency detection. It only used the picture-level label when training the network model. It divided the method into two stages. In the first stage, it trained the classification model according to the picture-level label to obtain the foreground inference graph. In the second stage, it processed the original image by super-pixel block and merged with the foreground inference graph obtained in phase one, thus refined significant object boundaries. The algorithm used existing large training sets and image-level tags, eliminated the use of pixel-level tags, which reduced the amount of annotation work. The experimental results on the four common benchmark datasets show that the performance is significantly better than the unsupervised model, and it has certain advantages compared with the full-supervised model.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.06.0576
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 2
Section: Technology of Graphic & Image
Pages: 601-605
Serial Number: 1001-3695(2020)02-063-0601-05

Publish History

[2020-02-05] Printed Article

Cite This Article

谭台哲, 轩康西, 曾群生. 基于图像级标签及超像素块的弱监督显著性检测 [J]. 计算机应用研究, 2020, 37 (2): 601-605. (Tan Taizhe, Xuan Kangxi, Zeng Qunsheng. Supervised significant detection based on image level labels and superpixel blocks [J]. Application Research of Computers, 2020, 37 (2): 601-605. )

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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.

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