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

doi:10.1016/j.patcog.2017.01.005

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 视频内容安全

	Diagnosing deep learning models for high accuracy age estimation from a single image
	Xing, Junhang 1; Li, Kai2 ; Hu, Weiming1,2 ; Yuan, Chunfeng1 ; Ling, Haibin 3
发表期刊	PATTERN RECOGNITION
	2017-06-01
卷号	66 期号:1 页码:106-116
文章类型	Article
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.
关键词	Age Estimation Deep Learning Multi-task Learning
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.patcog.2017.01.005
关键词[WOS]	FACE IMAGES
收录类别	SCI
语种	英语
项目资助者	973 Basic Research Program of China(2014CB349303) ; Natural Science Foundation of China(61472421, ; CAS(XDB02070003) ; U1636218 ; 61672519 ; 61303178)
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000397371800012
引用统计	被引频次：77[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/173211/15074
专题	多模态人工智能系统全国重点实验室_视频内容安全
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
第一作者单位	模式识别国家重点实验室
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.

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