Fine-grained image inpainting with scale-enhanced generative adversarial network

doi:10.1016/j.patrec.2020.12.008

CORC > 兰州理工大学 > 兰州理工大学 > 党委教师工作部（人事处、教师发展中心）

	Fine-grained image inpainting with scale-enhanced generative adversarial network
	Liu, Weirong 2; Cao, Chengrui 2; Liu, Jie 1; Ren, Chenwen 2; Wei, Yulin 2; Guo, Honglin 3
刊名	PATTERN RECOGNITION LETTERS
	2021
卷号	143 页码:81-87
关键词	Generative adversarial networks Fine-grained constraint Edge loss
ISSN号	0167-8655
DOI	10.1016/j.patrec.2020.12.008
英文摘要	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.
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000615785700012
内容类型	期刊论文
源URL	[http://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）
作者单位	1.Lanzhou Univ Technol, Natl Demonstrat Ctr Expt Elect & Control Engn Edu, Lanzhou, Gansu, Peoples R China; 2.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou, Gansu, Peoples R China; 3.Tianshui Elect Dr Res Inst Grp CO LTD, Tianshui, Gansu, Peoples R China
推荐引用方式 GB/T 7714	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.