Global and Local Consistent Wavelet-Domain Age Synthesis
文献类型：期刊论文
| 作者 | Li, Peipei1,2 ; Hu, Yibo1; He, Ran1,2; Sun, Zhenan1,2
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| 刊名 | IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
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| 出版日期 | 2019-11-01 |
| 卷号 | 14期号:11页码:2943-2957 |
| 关键词 | Age synthesis wavelet transform generative adversarial network global and local features |
| ISSN号 | 1556-6013 |
| DOI | 10.1109/TIFS.2019.2907973 |
| 通讯作者 | He, Ran(rhe@nlpr.ia.ac.cn) |
| 英文摘要 | Age synthesis is a challenging task due to the complicated and non-linear transformation in the human aging process. Aging information is usually reflected in local facial parts, such as wrinkles at the eye corners. However, these local facial parts contribute less in previous GAN-based methods for age synthesis. To address this issue, we propose a wavelet-domain global and local consistent age generative adversarial network (WaveletGLCA-GAN), in which one global specific network and three local specific networks are integrated together to capture both global topology information and local texture details of human faces. Different from the mast existing methods that modeling age synthesis in image domain, we adopt wavelet transform to depict the textual information in frequency domain. Moreover, five types of losses are adopted: 1) adversarial loss aims to generate realistic wavelets; 2) identity preserving loss aims to better preserve identity information; 3) age preserving loss aims to enhance the accuracy of age synthesis; 4) pixel-wise loss aims to preserve the background information of the input face; and 5) the total variation regularization aims to remove ghosting artifacts. Our method is evaluated on three face aging datasets, including CACD2000, Morph, and FG-NET. Qualitative and quantitative experiments show the superiority of the proposed method over other state-of-the-arts. |
| WOS关键词 | PERCEPTION |
| 资助项目 | State Key Development Program[2016YFB1001001] ; State Key Development Program[2017YFC0821602] ; State Key Development Program[2016YFB1001000] ; National Natural Science Foundation of China[61622310] ; National Natural Science Foundation of China[61427811] ; National Natural Science Foundation of China[61573360] ; Beijing Natural Science Foundation[JQ18017] |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000474549100001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | State Key Development Program ; National Natural Science Foundation of China ; Beijing Natural Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/26882]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | He, Ran |
| 作者单位 | 1.Inst Automat Chinese Acad Sci, Ctr Res Intelligent Percept & Comp, CAS Ctr Excellence Brain Sci & Intelligence Techn, Inst Automat,Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Peipei,Hu, Yibo,He, Ran,et al. Global and Local Consistent Wavelet-Domain Age Synthesis[J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,2019,14(11):2943-2957. |
| APA | Li, Peipei,Hu, Yibo,He, Ran,&Sun, Zhenan.(2019).Global and Local Consistent Wavelet-Domain Age Synthesis.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,14(11),2943-2957. |
| MLA | Li, Peipei,et al."Global and Local Consistent Wavelet-Domain Age Synthesis".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 14.11(2019):2943-2957. |
入库方式： OAI收割
来源：自动化研究所
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