CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算
Joint face alignment and segmentation via deep multi-task learning
Zhao, Yucheng1,2; Tang, Fan1,2; Dong, Weiming1; Huang, Feiyue3; Zhang, Xiaopeng1
发表期刊MULTIMEDIA TOOLS AND APPLICATIONS
ISSN1380-7501
2019-05-01
卷号78期号:10页码:13131-13148
通讯作者Dong, Weiming(weiming.dong@ia.ac.cn)
摘要Face alignment and segmentation are challenging problems which have been extensively studied in the field of multimedia. These two tasks are closely related and their learning processes are supposed to benefit each other. Hence, we present a joint multi-task learning algorithm for both face alignment and segmentation using deep convolutional neural network (CNN). The proposed multi-task learning approach allows CNN model to simultaneously share visual knowledge between different tasks. With a carefully designed refinement residual module, the cross-layer features are fused in a collaborative manner. To the best of our knowledge, this is the first time that face alignment and segmentation are learned together via deep multi-task learning. Our experiments show that learning these two related tasks simultaneously builds a synergy between them, improves the performance of each individual task, and rivals recent approaches. Furthermore, we demonstrate the effectiveness of our model in two practical applications: virtual makeup and face swap.
关键词Face alignment Face segmentation Multi-task learning Virtual makeup Face swap
DOI10.1007/s11042-018-5609-1
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[61672520] ; National Natural Science Foundation of China[61702488] ; National Natural Science Foundation of China[61501464] ; National Natural Science Foundation of China[6120106003] ; Beijing Natural Science Foundation[4162056] ; National Key Technology R&D Program of China[2015BAH53F02] ; CASIA-Tencent YouTu jointly research project ; National Natural Science Foundation of China[61672520] ; National Natural Science Foundation of China[61702488] ; National Natural Science Foundation of China[61501464] ; National Natural Science Foundation of China[6120106003] ; Beijing Natural Science Foundation[4162056] ; National Key Technology R&D Program of China[2015BAH53F02] ; CASIA-Tencent YouTu jointly research project
项目资助者National Natural Science Foundation of China ; Beijing Natural Science Foundation ; National Key Technology R&D Program of China ; CASIA-Tencent YouTu jointly research project
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000471654900022
出版者SPRINGER
七大方向——子方向分类图像视频处理与分析
引用统计
被引频次:14[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20889
专题模式识别国家重点实验室_多媒体计算
通讯作者Dong, Weiming
作者单位1.Chinese Acad Sci, Inst Automat, NLPR LIAMA, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Tencent, YouTu Lab, Shanghai, Peoples R China
第一作者单位模式识别国家重点实验室
通讯作者单位模式识别国家重点实验室
推荐引用方式
GB/T 7714
Zhao, Yucheng,Tang, Fan,Dong, Weiming,et al. Joint face alignment and segmentation via deep multi-task learning[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2019,78(10):13131-13148.
APA Zhao, Yucheng,Tang, Fan,Dong, Weiming,Huang, Feiyue,&Zhang, Xiaopeng.(2019).Joint face alignment and segmentation via deep multi-task learning.MULTIMEDIA TOOLS AND APPLICATIONS,78(10),13131-13148.
MLA Zhao, Yucheng,et al."Joint face alignment and segmentation via deep multi-task learning".MULTIMEDIA TOOLS AND APPLICATIONS 78.10(2019):13131-13148.
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