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Diagnosing deep learning models for high accuracy age estimation from a single image

文献类型：期刊论文

作者Xing, Junhang1; Li, Kai2; Hu, Weiming1,2; Yuan, Chunfeng1; Ling, Haibin3
刊名PATTERN RECOGNITION
出版日期2017-06-01
卷号66期号:1页码:106-116
关键词Age Estimation Deep Learning Multi-task Learning
DOI10.1016/j.patcog.2017.01.005
文献子类Article
英文摘要Given a face image, the problem of age estimation is to predict the actual age from the visual appearance of the face. In this work, we investigate this problem by means of the deep learning techniques. We comprehensively diagnose the training and evaluating procedures of the deep learning models for age estimation on two of the largest datasets. Our diagnosis includes three different kinds of formulations for the age estimation problem using five most representative loss functions, as well as three different architectures to incorporate multi-task learning with race and gender classification. We start our diagnoses process from a simple baseline architecture from previous work. With appropriate problem formulation and loss function, we obtain state-of-the-art performance with the simple baseline architecture. By further incorporating our newly proposed deep multitask learning architecture, the age estimation performance is further improved with high-accuracy race and gender classification results obtained simultaneously. With all the insights gained from the diagnosing process, we finally build a deep multi-task age estimation model which obtains a MAE of 2.96 on the Morph II dataset and 5.75 on the WebFace dataset, both of which improve previous best results by a large margin.
WOS关键词FACE IMAGES
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000397371800012
资助机构973 Basic Research Program of China(2014CB349303) ; Natural Science Foundation of China(61472421, ; CAS(XDB02070003) ; U1636218 ; 61672519 ; 61303178)
源URL[http://ir.ia.ac.cn/handle/173211/15074]  
专题自动化研究所_模式识别国家重点实验室_视频内容安全团队
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Chinese Acad Sci, Inst Automat, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China
3.Temple Univ, Dept Comp & Informat Sci, Philadelphia, PA 19122 USA
推荐引用方式
GB/T 7714		 Xing, Junhang,Li, Kai,Hu, Weiming,et al. Diagnosing deep learning models for high accuracy age estimation from a single image[J]. PATTERN RECOGNITION,2017,66(1):106-116.
APA Xing, Junhang,Li, Kai,Hu, Weiming,Yuan, Chunfeng,&Ling, Haibin.(2017).Diagnosing deep learning models for high accuracy age estimation from a single image.PATTERN RECOGNITION,66(1),106-116.
MLA Xing, Junhang,et al."Diagnosing deep learning models for high accuracy age estimation from a single image".PATTERN RECOGNITION 66.1(2017):106-116.

入库方式： OAI收割

来源：自动化研究所

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