Multi‐view frontal face image generation: A survey

Face images from different perspectives reduce the accuracy of face recognition, and the generation of frontal face images is an important research topic in the field of face recognition. To understand the development of frontal face generation models and grasp the current research hotspots and tren...

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Bibliographic Details
Published inConcurrency and computation Vol. 35; no. 18
Main Authors Ning, Xin, Nan, Fangzhe, Xu, Shaohui, Yu, Lina, Zhang, Liping
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 15.08.2023
Wiley Subscription Services, Inc
Subjects
3D model
deep learning
face frontalization
Face recognition
hybrid model
Image processing
Three dimensional models
Trends
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Summary:Face images from different perspectives reduce the accuracy of face recognition, and the generation of frontal face images is an important research topic in the field of face recognition. To understand the development of frontal face generation models and grasp the current research hotspots and trends, existing methods based on 3D models, deep learning, and hybrid models are summarized, and the current commonly used face generation methods are introduced. Dataset, and compare the performance of existing models through experiments. The purpose of this paper is to fundamentally understand the advantages of existing frontal face generation, sort out the key issues of such generation, and look toward future development trends.
Bibliography:Funding information
the National Natural Science Foundation of China, 61901436
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1532-0626
1532-0634
DOI:10.1002/cpe.6147