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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 1
9-14

Survey of facial completion techniques based on deep learning

Liu Ying1,2,3
She Jianchu1
Gong Yanchao1,3
Lu Jin1,3
Wang Fuping1,3
Lim Kengpang2,3,4
Li Yinghua1,3
1. Key Laboratory of Electronic Information Application Technology for Crime Scene Investigation, Ministry of Public Security, Xi'an 710121, China
2. International Cooperation Research Center for Wireless Communication & Information Processing Technology, Xi'an 710121, China
3. Center for Image & Information Processing, Xi'an University of Posts & Telecommunications, Xi'an 710121, China
4. Xsecpro Pte. Ltd. , Singapore 787820, Singapore
DOI: 10.19734/j.issn.1001-3695.2019.10.0583

Abstract

Traditional image inpainting algorithms cannot accurately capture high-level semantics when regions involve complex non-repetitive structures, such as faces. In the past three years, the method based on deep learning has been applied to image inpainting, and the structural similarity of the repair results had increased by more than 10% compared with the traditional methods. This paper firstly expounded the research and development process of facial completion technologies, mainly introduced the face repair algorithm based on deep learning, which was divided into unsupervised and supervised categories. In each category, it focused on the various facial completion algorithm ideas that had emerged in recent years. Then it summarized the six mainstream types of image datasets. Two evaluation indexes were summarized in this paper. Finally, it discussed the future research direction of facial completion technique.

Foundation Support

国家自然科学基金资助项目(61801381)
陕西省国际合作交流项目(2018KW-003)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.10.0583
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 1
Section: Survey
Pages: 9-14
Serial Number: 1001-3695(2021)01-002-0009-06

Publish History

[2021-01-05] Printed Article

Cite This Article

刘颖, 佘建初, 公衍超, 等. 基于深度学习的面部修复技术综述 [J]. 计算机应用研究, 2021, 38 (1): 9-14. (Liu Ying, She Jianchu, Gong Yanchao, et al. Survey of facial completion techniques based on deep learning [J]. Application Research of Computers, 2021, 38 (1): 9-14. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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