28 citations · 56 across the 6 of their papers we have counts for
10 papers
A Learnable Optimization and Regularization Approach to Massive MIMO CSI Feedback
Zhengyang Hu, Guanzhang Liu, Qi Xie +3
Channel state information (CSI) plays a critical role in achieving the potential benefits of massive multiple input multiple output (MIMO) systems. In frequency division duplex (FD…
KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution
Jiahong Fu, Hong Wang, Qi Xie +3
Although current deep learning-based methods have gained promising performance in the blind single image super-resolution (SISR) task, most of them mainly focus on heuristically co…
Low-light Image Enhancement by Retinex Based Algorithm Unrolling and Adjustment
Xinyi Liu, Qi Xie, Qian Zhao +2
Motivated by their recent advances, deep learning techniques have been widely applied to low-light image enhancement (LIE) problem. Among which, Retinex theory based ones, mostly f…
From Rain Generation to Rain Removal
Hong Wang, Zongsheng Yue, Qi Xie +3
For the single image rain removal (SIRR) task, the performance of deep learning (DL)-based methods is mainly affected by the designed deraining models and training datasets. Most o…
Structural Residual Learning for Single Image Rain Removal
Hong Wang, Yichen Wu, Qi Xie +3
To alleviate the adverse effect of rain streaks in image processing tasks, CNN-based single image rain removal methods have been recently proposed. However, the performance of thes…
A Model-driven Deep Neural Network for Single Image Rain Removal
Hong Wang, Qi Xie, Qian Zhao +1
Deep learning (DL) methods have achieved state-of-the-art performance in the task of single image rain removal. Most of current DL architectures, however, are still lack of suffici…