Generating and Editing Arbitrary Facial Images by Learning Feature Axis
文献类型：期刊论文
| 作者 | Yang N(杨楠)3,4,5 ; Xu YY(许原野)3,4,5; Zheng ZY(郑泽宇)3,4,5; Qi, Liang2; Guo XW(郭希旺)1,6; Wang TR(王天然)3,4
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| 刊名 | IEEE ACCESS
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| 出版日期 | 2020 |
| 卷号 | 8页码:135468-135478 |
| ISSN号 | 2169-3536 |
| 关键词 | Mathematical model Gallium nitride Computational modeling Training Generators Decoding Generative adversarial networks Deep learning generative adversarial networks image generating image editing |
| 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] |
| 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.Computer and Communication Engineering College, Liaoning Shihua University, Fushun 113001, China 2.Department of Intelligent Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China 3.University of Chinese Academy of Sciences, Beijing 100049, China 4.Institutes for Robotics and Intelligent Manufacturing, Shenyang 110016, China 5.Department of Digital Factory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 6.Helen and John C. Hartmann Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA |
| 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. |
入库方式： OAI收割
来源：沈阳自动化研究所
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