Facial Age and Expression Synthesis Using Ordinal Ranking Adversarial Networks

doi:10.1109/TIFS.2020.2980792

CASIA OpenIR > 智能感知与计算研究中心

	Facial Age and Expression Synthesis Using Ordinal Ranking Adversarial Networks
	Sun, Yunlian 1; Tang, Jinhui 1; Sun, Zhenan2,3,4 ; Tistarelli, Massimo 5
发表期刊	IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
ISSN	1556-6013
	2020
卷号	15 页码:2960-2972
通讯作者	Tang, Jinhui(jinhuitang@njust.edu.cn)
摘要	Facial image synthesis has been extensively studied, for a long time, in both computer graphics and computer vision. Particularly, the synthesis of face images with varying ages, expressions and poses has received an increasing attention owing to several real-world applications. In this paper, facial age and expression synthesis are addressed. While previous and current research papers on facial age synthesis mostly adopt an age span of 10 years, this paper investigates face aging with a shorter time span. For expression synthesis, given a neutral face, we work on synthesizing faces with varying expression intensities (e.g., from zero to high). Note that both human ages and expression intensities are inherently ordinal. To fully exploit this ordinal nature, we devise ordinal ranking generative adversarial networks (ranking GAN). For each face, a one-hot label is assigned to define its age range/expression intensity. By exploiting the relative order information among age ranges/expression intensities, a binary ranking vector is further computed for each face. In ranking GAN, one-hot labels are used as the condition of the generator for synthesizing faces with target age groups/expression intensities. Moreover, we add a sequence of cost-sensitive ordinal rankers on top of several multi-scale discriminators, with the aim of minimizing age/intensity rank estimation loss when optimizing both the generator and discriminators. In order to evaluate the proposed ranking GAN, extensive experiments are carried out on several public face databases. As demonstrated by the experimental testing, this ranking scheme performs well even when the amount of available labeled training data is limited. The reported experimental results well demonstrate the effectiveness of ranking GAN on synthesizing face aging sequences and faces with varying expression intensities.
关键词	Face image aging facial expression synthesis generative adversarial networks ordinal ranking
DOI	10.1109/TIFS.2020.2980792
关键词[WOS]	MANIPULATION ; APPEARANCE ; PERCEPTION ; FACES ; MODEL ; SHAPE
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2016YFB1001001] ; National Natural Science Foundation of China[61603391] ; National Natural Science Foundation of China[61925204] ; National Natural Science Foundation of China[61427811] ; Italian Ministry of Research
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Italian Ministry of Research
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000524505300007
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：8[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/173211/38917
专题	智能感知与计算研究中心
通讯作者	Tang, Jinhui
作者单位	1.Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, Nanjing 210094, Peoples R China 2.Chinese Acad Sci, Ctr Res Intelligent Percept & Comp, Inst Automat, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China 5.Univ Sassari, Dept Sci & Informat Technol, I-07100 Sassari, Italy
推荐引用方式 GB/T 7714	Sun, Yunlian,Tang, Jinhui,Sun, Zhenan,et al. Facial Age and Expression Synthesis Using Ordinal Ranking Adversarial Networks[J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,2020,15:2960-2972.
APA	Sun, Yunlian,Tang, Jinhui,Sun, Zhenan,&Tistarelli, Massimo.(2020).Facial Age and Expression Synthesis Using Ordinal Ranking Adversarial Networks.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,15,2960-2972.
MLA	Sun, Yunlian,et al."Facial Age and Expression Synthesis Using Ordinal Ranking Adversarial Networks".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 15(2020):2960-2972.