Feature-Improving Generative Adversarial Network for Face Frontalization

Face frontalization can boost the performance of face recognition methods and has made significant progress with the development of Generative Adversarial Networks (GANs). However, many GAN-based face frontalization methods still perform relatively weak on face recognition tasks under large face pos...

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Bibliographic Details
Main Authors: Changle Rong, Xingming Zhang, Yubei Lin
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9057608/