Fine-grained image inpainting with scale-enhanced generative adversarial network
Liu, Weirong1; Cao, Chengrui1; Liu, Jie2; Ren, Chenwen1; Wei, Yulin1; Guo, Honglin3
2021-03
发表期刊PATTERN RECOGNITION LETTERS
ISSN0167-8655
卷号143页码:81-87
摘要With the emergence of Generative Adversarial Networks, great progress has been made in image inpainting. However, most existing methods can produce plausible results, but fail to generate finer textures and structures. This is mainly due to the fact that (1) the generation of finer content in the masked region of an image is not constrained enough during network training, and (2) many different alternative pixels are exist to fill in the masked regions, making it very difficult for the inpainting network to generate reasonable sharp edges. To address these issues, we propose a Scale Enhanced GAN (SE-GAN) model which combines the constraints of large- and small-scale receptive fields of our tailor-made discriminators to achieve fine-grained constraint on image details, a novel edge loss to further ensure the sharpness of the generated image. Experiments on multiple datasets including faces(CelebA-HQ), textures(DTD), buildings(Facade) and natural images(ImageNet, Places2) show that our approach can generate higher quality inpainting results with more details than previous methods. (c) 2021 Elsevier B.V. All rights reserved.
关键词Generative adversarial networks Fine-grained constraint Edge loss
DOI10.1016/j.patrec.2020.12.008
收录类别SCIE
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000615785700012
出版者ELSEVIER
EI入藏号20210509869479
EI主题词Image enhancement
来源库WOS
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被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符https://ir.lut.edu.cn/handle/2XXMBERH/147451
专题党委教师工作部(人事处、教师发展中心)
通讯作者Liu, Weirong
作者单位1.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou, Gansu, Peoples R China;
2.Lanzhou Univ Technol, Natl Demonstrat Ctr Expt Elect & Control Engn Edu, Lanzhou, Gansu, Peoples R China;
3.Tianshui Elect Dr Res Inst Grp CO LTD, Tianshui, Gansu, Peoples R China
第一作者单位电气工程与信息工程学院
通讯作者单位电气工程与信息工程学院
第一作者的第一单位电气工程与信息工程学院
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Liu, Weirong,Cao, Chengrui,Liu, Jie,et al. Fine-grained image inpainting with scale-enhanced generative adversarial network[J]. PATTERN RECOGNITION LETTERS,2021,143:81-87.
APA Liu, Weirong,Cao, Chengrui,Liu, Jie,Ren, Chenwen,Wei, Yulin,&Guo, Honglin.(2021).Fine-grained image inpainting with scale-enhanced generative adversarial network.PATTERN RECOGNITION LETTERS,143,81-87.
MLA Liu, Weirong,et al."Fine-grained image inpainting with scale-enhanced generative adversarial network".PATTERN RECOGNITION LETTERS 143(2021):81-87.
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