Super-resolution Reconstruction of Mosaic Face Images Based on GAN

Xu Yonghui; Yang Gaobo

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Super-resolution Reconstruction of Mosaic Face Images Based on GAN

Xu Yonghui 1,Yang Gaobo 2 *

1.College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082;College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082

*Correspondence author

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Funding: none

Opened online:18 May 2020

Accepted by: none

Citation: Xu Yonghui,Yang Gaobo.Super-resolution Reconstruction of Mosaic Face Images Based on GAN[OL]. [18 May 2020] http://en.paper.edu.cn/en_releasepaper/content/4752050

With the rapid development of artificial intelligence technologies, image super-resolution which is one of the hottest topics in computer vision community, has achieved attractive progresses. To restore mosaic face images, we present an effective model, namely DemosaicGAN. It combines existing SRGAN and RDN and optimizes the perceptual loss functions. As far as we concerned, our experimental results show that the proposed DemosaicGAN achieves the best results in super-resolution reconstruction of mosaic face images so far.

Keywords:Computer Application Technology; Image Super-resolution; Image Mosaic; Face restoration; Generative Adversarial Network

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