TY - GEN
T1 - High-quality face image super-resolution based on Generative Adversarial Networks
AU - Zhong, Xinru
AU - Qu, Xiujie
AU - Chen, Chen
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Face image super-resolution has received increasing attention. However, since the face has a lot of fine textures, it is very difficult to rebuild for large upscaling factors. We propose a new method for face image SR, using residul dense block(RDB) as the basic unit and the Inception architecture is combined in the low layers. We use the relativistic GAN and the improved perceptual loss defined by the features before activation.For the large scaling factors, our GAN is progressive both in architecture and training. The network proposed achieves excellent performance in the reconstruction of low-resolution face images, especially under large scaling factors such as 4x and 8x.
AB - Face image super-resolution has received increasing attention. However, since the face has a lot of fine textures, it is very difficult to rebuild for large upscaling factors. We propose a new method for face image SR, using residul dense block(RDB) as the basic unit and the Inception architecture is combined in the low layers. We use the relativistic GAN and the improved perceptual loss defined by the features before activation.For the large scaling factors, our GAN is progressive both in architecture and training. The network proposed achieves excellent performance in the reconstruction of low-resolution face images, especially under large scaling factors such as 4x and 8x.
KW - face image super-resolution
KW - progressive trainging
KW - relativistic Generative Adversarial Networks
UR - https://www.scopus.com/pages/publications/85081172504
U2 - 10.1109/IAEAC47372.2019.8998075
DO - 10.1109/IAEAC47372.2019.8998075
M3 - Conference contribution
AN - SCOPUS:85081172504
T3 - Proceedings of 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019
SP - 1178
EP - 1182
BT - Proceedings of 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019
A2 - Xu, Bing
A2 - Mou, Kefen
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2019
Y2 - 20 December 2019 through 22 December 2019
ER -