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
2018-01
期号pp页码:1-18
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 multitask 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
引用统计
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_多媒体计算与图形学
作者单位1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.YouTu Lab, Tencent
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,2018(pp):1-18.
APA Zhao Yucheng,Tang Fan,Dong Weiming,Huang Feiyue,&Zhang Xiaopeng.(2018).Joint Face Alignment and Segmentation via Deep Multi-task Learning.Multimedia Tools and Applications(pp),1-18.
MLA Zhao Yucheng,et al."Joint Face Alignment and Segmentation via Deep Multi-task Learning".Multimedia Tools and Applications .pp(2018):1-18.
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