中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 多模态人工智能系统全国重点实验室
  5. 生物识别与安全技术研究中心
Region-Based Context Enhanced Network for Robust Multiple Face Alignment

文献类型：期刊论文

作者Lin, Xuxin1; Liang, Yanyan1; Wan, Jun3; Lin, Chi2; Li, Stan Z.3
刊名IEEE TRANSACTIONS ON MULTIMEDIA
出版日期2019-12-01
卷号21期号:12页码:3053-3067
ISSN号1520-9210
关键词Facial landmark localization face alignment convolutional network point distribution model
DOI10.1109/TMM.2019.2916455
通讯作者Liang, Yanyan(yyliang@must.edu.mo)
英文摘要The recent studies for face alignment have involved developing an isolated algorithm on well-cropped face images. It is difficult to obtain the expected input by using an off-the-shelf face detector in practical applications. In this paper, we attempt to bridge between face detection and face alignment by establishing a novel joint multi-task model, which allows us to simultaneously detect multiple faces and their landmarks on a given scene image. In contrast to the pipeline-based framework by cascading separate models, we aim to propose an end-to-end convolutional network by sharing and transform feature representations between the task-specific modules. To learn a robust landmark estimator for unconstrained face alignment, three types of context enhanced blocks are designed to encode feature maps with multi-level context, multi-scale context, and global context. In the post-processing step, we develop a shape reconstruction algorithm based on point distribution model to refine the landmark outliers. Extensive experiments demonstrate that our results are robust for the landmark location task and insensitive to the location of estimated face regions. Furthermore, our method significantly outperforms recent state-of-the-art methods on several challenging datasets including 300 W, AFLW, and COFW.
WOS关键词FACIAL LANDMARK DETECTION
资助项目National Key Research and Development Plan[2016YFC0801002] ; Chinese National Natural Science Foundation[61876179] ; Chinese National Natural Science Foundation[61872367] ; Science and Technology Development Fund of Macau[152/2017/A] ; Science and Technology Development Fund of Macau[0025/2018/A1] ; Science and Technology Development Fund of Macau[008/2019/A1]
WOS研究方向Computer Science ; Telecommunications
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000512345200007
资助机构National Key Research and Development Plan ; Chinese National Natural Science Foundation ; Science and Technology Development Fund of Macau
源URL[http://ir.ia.ac.cn/handle/173211/28584]  
专题自动化研究所_模式识别国家重点实验室_生物识别与安全技术研究中心
通讯作者Liang, Yanyan
作者单位1.Macau Univ Sci & Technol, Fac Informat Technol, Taipa, Macau, Peoples R China
2.Univ Southern Calif, Los Angeles, CA 90007 USA
3.Chinese Acad Sci, Inst Automat, Res & Natl Lab Pattern Recognit, Ctr Biometr & Secur, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Lin, Xuxin,Liang, Yanyan,Wan, Jun,et al. Region-Based Context Enhanced Network for Robust Multiple Face Alignment[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2019,21(12):3053-3067.
APA Lin, Xuxin,Liang, Yanyan,Wan, Jun,Lin, Chi,&Li, Stan Z..(2019).Region-Based Context Enhanced Network for Robust Multiple Face Alignment.IEEE TRANSACTIONS ON MULTIMEDIA,21(12),3053-3067.
MLA Lin, Xuxin,et al."Region-Based Context Enhanced Network for Robust Multiple Face Alignment".IEEE TRANSACTIONS ON MULTIMEDIA 21.12(2019):3053-3067.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。