Perception-oriented Single Image Super-Resolution via Dual Relativistic Average Generative Adversarial Networks

no code implementations • 8 Nov 2019 • Yuan Ma, Kewen Liu, Hongxia Xiong, Panpan Fang, Xiaojun Li, Yalei Chen, Chaoyang Liu

The presence of residual and dense neural networks which greatly promotes the development of image Super-Resolution(SR) have witnessed a lot of impressive results.

Image Super-Resolution SSIM

Single Image Super-resolution via Dense Blended Attention Generative Adversarial Network for Clinical Diagnosis

no code implementations • 15 Jun 2019 • Kewen Liu, Yuan Ma, Hongxia Xiong, Zejun Yan, Zhijun Zhou, Chaoyang Liu, Panpan Fang, Xiaojun Li, Yalei Chen

Futhermore, we abandoned this paper due to its limitation only applied on medical images.

Generative Adversarial Network Image Super-Resolution

Medical image super-resolution method based on dense blended attention network

no code implementations • 13 May 2019 • Kewen Liu, Yuan Ma, Hongxia Xiong, Zejun Yan, Zhijun Zhou, Panpan Fang, Chaoyang Liu

In order to address the issue that medical image would suffer from severe blurring caused by the lack of high-frequency details in the process of image super-resolution reconstruction, a novel medical image super-resolution method based on dense neural network and blended attention mechanism is proposed.

Image Super-Resolution SSIM