Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 7
2223-2228

Text-guided image inpainting with deep fusion of image text features

Lan Hong
Guo Fucheng
College of Information Engineering, Jiangxi University of Science & Technology, Ganzhou Jiangxi 341000, China
DOI: 10.19734/j.issn.1001-3695.2022.10.0528

Abstract

In order to solve the problem that the existing text guided image inpainting models lack efficient fusion of information between modes when dealing with text image fusion, resulting in unreal repair results and poor semantic consistency, this paper proposed a text guided image inpainting model BATF, which integrated image text features through conditional batch normalization. Firstly, it normalized the damaged and undamaged regions respectively by the spatial region normalization encoder to reduce the influence of direct feature normalization on the mean variance shift. Secondly, through the depth affine transformation, it fused the extracted image features and the text feature vectors to enhance the visual semantic embedding of the generator network feature map, so that the image and the features could be fused more effectively. Finally, it designed an efficient discriminator and introduced a target perception discriminator in this paper to enhance the texture authenticity and semantic consistency of the repaired image. Quantitative and qualitative experiments on CUB bird, a text-labeled dataset, show that the proposed model achieves 20.86, 0.836, and 23.832 for PSNR, SSIM, and MAE, respectively. BATF model is better than the existing models MMFL and ALMR, and the repaired images both meet the requirements of given text attributes and have high semantic consistency.

Foundation Support

2021年江西省研究生创新专项资金资助项目(YC2021-S582)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.10.0528
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 7
Section: Technology of Graphic & Image
Pages: 2223-2228
Serial Number: 1001-3695(2023)07-046-2223-06

Publish History

[2023-01-05] Accepted Paper
[2023-07-05] Printed Article

Cite This Article

兰红, 郭福城. 深度融合图像文本特征的文本引导图像修复 [J]. 计算机应用研究, 2023, 40 (7): 2223-2228. (Lan Hong, Guo Fucheng. Text-guided image inpainting with deep fusion of image text features [J]. Application Research of Computers, 2023, 40 (7): 2223-2228. )

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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