Generating and Editing Arbitrary Facial Images by Learning Feature Axis

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 数字工厂研究室

	Generating and Editing Arbitrary Facial Images by Learning Feature Axis
	Yang N(杨楠)1,2,3; Xu YY(许原野)1,2,3; Zheng ZY(郑泽宇)1,2,3; Qi, Liang 4; Guo XW(郭希旺)5,6; Wang TR(王天然)1,2
刊名	IEEE ACCESS
	2020
卷号	8 页码:135468-135478
关键词	Mathematical model Gallium nitride Computational modeling Training Generators Decoding Generative adversarial networks Deep learning generative adversarial networks image generating image editing
ISSN号	2169-3536
产权排序	1
英文摘要	There are mainly three limitations of the traditional facial attribute editing techniques: 1) incapability of generating an arbitrary facial image with high-resolution; 2) being unable to generate and edit new facial images synthesized by the computer and 3) limited diversity of edited images. This paper presents a method for generating and editing images simultaneously. It incorporates a high-resolution facial image generator, a multi-label classifier, and a Generalized Linear Model (GLM). Experimental results show that our method can generate arbitrary high-resolution facial images, edit computer-synthesized images, perform multi-attribute editing, and effectively control the intensity and style of the generated images. Besides, the approach has high efficiency and flexibility, allowing rapid migration of attribute information from the data set. We design a graphical interface program, which can be integrated as a mobile application.
资助项目	National Key Research and Development Program of China[2018YFF0214704] ; National Natural Science Foundation of China[61803367] ; National Natural Science Foundation of China[61573089] ; National Natural Science Foundation of China[61903229] ; National Natural Science Foundation of China[61973180] ; Natural Science Foundation of Liaoning Province[2019-MS-346] ; Liaoning Revitalization Talents Program[XLYC1907166] ; Liaoning Province Department of Education Foundation of China[L2019027] ; Natural Science Foundation of Shandong Province[ZR2019BF004] ; Natural Science Foundation of Shandong Province[ZR2019BF041]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
语种	英语
WOS记录号	WOS:000554893600001
资助机构	National Key Research and Development Program of China [2018YFF0214704] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [61803367, 61573089, 61903229, 61973180] ; Natural Science Foundation of Liaoning ProvinceNatural Science Foundation of Liaoning Province [2019-MS-346] ; Liaoning Revitalization Talents Program [XLYC1907166] ; Liaoning Province Department of Education Foundation of China [L2019027] ; Natural Science Foundation of Shandong ProvinceNatural Science Foundation of Shandong Province [ZR2019BF004, ZR2019BF041]
内容类型	期刊论文
源URL	[http://ir.sia.cn/handle/173321/27476]
专题	沈阳自动化研究所_数字工厂研究室
通讯作者	Zheng ZY(郑泽宇); Qi, Liang
作者单位	1.Institutes for Robotics and Intelligent Manufacturing, Shenyang 110016, China 2.University of Chinese Academy of Sciences, Beijing 100049, China 3.Department of Digital Factory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 4.Department of Intelligent Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China 5.Helen and John C. Hartmann Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA 6.Computer and Communication Engineering College, Liaoning Shihua University, Fushun 113001, China
推荐引用方式 GB/T 7714	Yang N,Xu YY,Zheng ZY,et al. Generating and Editing Arbitrary Facial Images by Learning Feature Axis[J]. IEEE ACCESS,2020,8:135468-135478.
APA	Yang N,Xu YY,Zheng ZY,Qi, Liang,Guo XW,&Wang TR.(2020).Generating and Editing Arbitrary Facial Images by Learning Feature Axis.IEEE ACCESS,8,135468-135478.
MLA	Yang N,et al."Generating and Editing Arbitrary Facial Images by Learning Feature Axis".IEEE ACCESS 8(2020):135468-135478.