Deeply Supervised Face Completion With Multi-Context Generative Adversarial Network
文献类型：期刊论文
| 作者 | Tang YD(唐延东)2,3 ; Fan HJ(范慧杰)2,3; Wang Q(王强)1,2,3; Zhu LL(朱琳琳)4
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| 刊名 | IEEE SIGNAL PROCESSING LETTERS
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| 出版日期 | 2019 |
| 卷号 | 26期号:3页码:400-404 |
| 关键词 | Face completion multi-context generative adversarial network |
| ISSN号 | 1070-9908 |
| 产权排序 | 1 |
| 英文摘要 | Recent face completion works have achieved significant improvement using generative adversarial networks (GANs). There are still two important issues in this challenging task: first, semantic understanding; and second, high-frequency details prediction. In this letter, we propose a unified model by introducing multicontext structures within GANs. Our model, named multi-context generative adversarial networks (MCGAN), automatically learns the hierarchical appearances of a corrupted image and predicted the missing regions from different perspectives. In this model, semantic understanding and high-frequency details are both taken into account and modeled with two parallel networks, respectively. While one learns the semantic understanding of the input face image at a high level, the other extracts low-level features for highfrequency details prediction. Our MCGAN takes full advantage of multi-scale features learned from two complementary networks and generates semantically new pixels for the missing region with fine details. Extensive quantitative and qualitative experiments on benchmark datasets show that the proposed model outperforms several state-of-the-art models. |
| 资助项目 | National Natural Science Foundation of China[61873259] ; National Natural Science Foundation of China[61333019] ; National Natural Science Foundation of China[61503256] ; State Key Laboratory of Robotics Open Project[2015-212] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000457376100001 |
| 资助机构 | National Natural Science Foundation of China ; State Key Laboratory of Robotics Open Project |
| 源URL | [http://ir.sia.cn/handle/173321/24154]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Fan HJ(范慧杰) |
| 作者单位 | 1.University of Chinese Academy of Sciences, Beijing 100049, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 3.Institute of Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 4.College of Automation, Shenyang Aerospace University, Shenyang 110136, China |
| 推荐引用方式 GB/T 7714 | Tang YD,Fan HJ,Wang Q,et al. Deeply Supervised Face Completion With Multi-Context Generative Adversarial Network[J]. IEEE SIGNAL PROCESSING LETTERS,2019,26(3):400-404. |
| APA | Tang YD,Fan HJ,Wang Q,&Zhu LL.(2019).Deeply Supervised Face Completion With Multi-Context Generative Adversarial Network.IEEE SIGNAL PROCESSING LETTERS,26(3),400-404. |
| MLA | Tang YD,et al."Deeply Supervised Face Completion With Multi-Context Generative Adversarial Network".IEEE SIGNAL PROCESSING LETTERS 26.3(2019):400-404. |
入库方式： OAI收割
来源：沈阳自动化研究所
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