Author(s): Ning, X (Ning, Xin); Nan, FZ (Nan, Fangzhe); Xu, SH (Xu, Shaohui); Yu, LN (Yu, Lina); Zhang, LP (Zhang, Liping)

Source: CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE Article Number: e6147 DOI: 10.1002/cpe.6147 Early Access Date: DEC 2020

Abstract: 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.

Accession Number: WOS:000599518000001

ISSN: 1532-0626

eISSN: 1532-0634

Full Text: https://onlinelibrary.wiley.com/doi/10.1002/cpe.6147