15 citations · 27 across the 7 of their papers we have counts for
7 papers
The Second LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results
Xiang Chen, Hao Li, Jiangxin Dong +89
This paper presents a review of the second LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aims to advance unified image restoration under diverse real-wo…
LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results
Xiang Chen, Hao Li, Jiangxin Dong +54
This paper presents a review for the LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aimed to advance research on real-world all-in-one image restoration…
Spatio-Temporal Difference Guided Motion Deblurring with the Complementary Vision Sensor
Yapeng Meng, Lin Yang, Yuguo Chen +6
Motion blur arises when rapid scene changes occur during the exposure period, collapsing rich intra-exposure motion into a single RGB frame. Without explicit structural or temporal…
Learning A Sparse Transformer Network for Effective Image Deraining
Xiang Chen, Hao Li, Mingqiang Li +1
Transformers-based methods have achieved significant performance in image deraining as they can model the non-local information which is vital for high-quality image reconstruction…
Unpaired Deep Image Dehazing Using Contrastive Disentanglement Learning
Xiang Chen, Zhentao Fan, Pengpeng Li +5
We offer a practical unpaired learning based image dehazing network from an unpaired set of clear and hazy images. This paper provides a new perspective to treat image dehazing as…
Unpaired Deep Image Deraining Using Dual Contrastive Learning
Xiang Chen, Jinshan Pan, Kui Jiang +5
Learning single image deraining (SID) networks from an unpaired set of clean and rainy images is practical and valuable as acquiring paired real-world data is almost infeasible. Ho…
Multi-Scale Hourglass Hierarchical Fusion Network for Single Image Deraining
Xiang Chen, Yufeng Huang, Lei Xu
Rain streaks bring serious blurring and visual quality degradation, which often vary in size, direction and density. Current CNN-based methods achieve encouraging performance, whil…