activity
20202022
most citedStructural Residual Learning for Single Image Rain Removal

4 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

Spatial-Temporal Attention Network for Open-Set Fine-Grained Image Recognition

Jiayin Sun, Hong Wang, Qiulei Dong

Triggered by the success of transformers in various visual tasks, the spatial self-attention mechanism has recently attracted more and more attention in the computer vision communi…

cs.CV20221 cited

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…

eess.IV20213 cited

InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction

Hong Wang, Yuexiang Li, Haimiao Zhang +4

For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods have achieved promising performances, most of them suffer from two problems: 1) the CT ima…

cs.CV2020

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…

eess.IV20204 cited

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…