Institutional Repository of Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
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 |
ISSN | 1380-7501 |
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 |
DOI | 10.1007/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 | |
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. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Joint face alignment(3380KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 |
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