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Two-Stream Deep Correlation Network for Frontal Face Recovery

文献类型：期刊论文

作者Zhang, Ting1,2; Dong, Qiulei1,2,3; Tang, Ming1; Hu, Zhanyi1,2,3
刊名IEEE SIGNAL PROCESSING LETTERS
出版日期2017-10-01
卷号24期号:10页码:1478-1482
关键词Correlation Layer Deep Neural Network Frontal Face Recovery Geometric Stream Textural Stream
DOI10.1109/LSP.2017.2736542
文献子类Article
英文摘要Pose and textural variations are two dominant factors to affect the performance of face recognition. It is widely believed that generating the corresponding frontal face froma face image of an arbitrary pose is an effective step toward improving the recognition performance. In the literature, however, the frontal face is generally recovered by only exploring textural characteristic. In this letter, we propose a two-stream deep correlation network, which incorporates both geometric and textural features for frontal face recovery. Given a face image under an arbitrary pose as input, geometric and textural characteristics are first extracted from two separate streams. The extracted characteristics are then fused through the proposed multiplicative patch correlation layer. These two steps are integrated into one network for end-to-end training and prediction, which is demonstrated effective compared with state-of-the-art methods on the benchmark datasets.
WOS关键词RECOGNITION ; IDENTITY ; SPACE ; MODEL
WOS研究方向Engineering
语种英语
WOS记录号WOS:000408775600006
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences(XDB02070002) ; National Natural Science Foundation of China(61421004 ; 61375042 ; 61573359)
源URL[http://ir.ia.ac.cn/handle/173211/19712]  
专题自动化研究所_模式识别国家重点实验室_机器人视觉团队
通讯作者Dong, Qiulei
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Ting,Dong, Qiulei,Tang, Ming,et al. Two-Stream Deep Correlation Network for Frontal Face Recovery[J]. IEEE SIGNAL PROCESSING LETTERS,2017,24(10):1478-1482.
APA Zhang, Ting,Dong, Qiulei,Tang, Ming,&Hu, Zhanyi.(2017).Two-Stream Deep Correlation Network for Frontal Face Recovery.IEEE SIGNAL PROCESSING LETTERS,24(10),1478-1482.
MLA Zhang, Ting,et al."Two-Stream Deep Correlation Network for Frontal Face Recovery".IEEE SIGNAL PROCESSING LETTERS 24.10(2017):1478-1482.

入库方式： OAI收割

来源：自动化研究所

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