Facial Expression Transfer Based on Conditional Generative Adversarial Networks

With the development of computer vision and image transfer, facial expression transfer has been more and more widespread applications. But there are still some problems, such as lack of realistic expression, poor retention of facial identity features and low synthesis efficiency. In order to solve t...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Yang Fan, Xingguo Jiang, Shuxing Lan, Jianghai Lan
Format:	Article
Language:	English
Published:	IEEE 2023-01-01
Subjects:	Face features facial expression transfer conditional generative adversarial networks U-net face editing
Online Access:	https://ieeexplore.ieee.org/document/10179928/