CASIA OpenIR
3D Aided Duet GANs for Multi-View Face Image Synthesis
Cao, Jie1,2; Hu, Yibo1,2; Yu, Bing3; He, Ran1,2; Sun, Zhenan1,2
Source PublicationIEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
ISSN1556-6013
2019-08-01
Volume14Issue:8Pages:2028-2042
Corresponding AuthorCao, Jie(jie.cao@cripac.ia.ac.cn)
AbstractMulti-view face synthesis from a single image is an ill-posed computer vision problem. It often suffers from appearance distortions if it is not well-defined. Producing photo-realistic and identity preserving multi-view results is still a not well-defined synthesis problem. This paper proposes 3D aided duet generative adversarial networks (AD-GAN) to precisely rotate the yaw angle of an input face image to any specified angle. AD-GAN decomposes the challenging synthesis problem into two well-constrained subtasks that correspond to a face normalizer and a face editor. The normalizer first frontalizes an input image, and then the editor rotates the frontalized image to a desired pose guided by a remote code. In the meantime, the face normalizer is designed to estimate a novel dense UV correspondence field, making our model aware of 3D face geometry information. In order to generate photo-realistic local details and accelerate convergence process, the normalizer and the editor are trained in a two-stage manner and regulated by a conditional self-cycle loss and a perceptual loss. Exhaustive experiments on both controlled and uncontrolled environments demonstrate that the proposed method not only improves the visual realism of multi-view synthetic images but also preserves identity information well.
KeywordFace rotation and frontalization multi-view face synthesis pose-invariant face recognition face reconstruction
DOI10.1109/TIFS.2019.2891116
WOS KeywordSHAPE
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[U1836217] ; National Natural Science Foundation of China[61427811] ; National Natural Science Foundation of China[61573360] ; National Natural Science Foundation of China[61721004] ; National Key Research and Development Program of China[2017YFC0821602]
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program of China
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000467523400006
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/24596
Collection中国科学院自动化研究所
Corresponding AuthorCao, Jie
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Res Intelligent Percept & Comp,Ctr Excellence, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 101408, Peoples R China
3.Huawei Technol Co Ltd, Noahs Ark Lab, Beijing 100085, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Cao, Jie,Hu, Yibo,Yu, Bing,et al. 3D Aided Duet GANs for Multi-View Face Image Synthesis[J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,2019,14(8):2028-2042.
APA Cao, Jie,Hu, Yibo,Yu, Bing,He, Ran,&Sun, Zhenan.(2019).3D Aided Duet GANs for Multi-View Face Image Synthesis.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,14(8),2028-2042.
MLA Cao, Jie,et al."3D Aided Duet GANs for Multi-View Face Image Synthesis".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 14.8(2019):2028-2042.
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