11 citations · 19 across the 4 of their papers we have counts for
6 papers · 1 filter
Unsupervised Low-light Image Enhancement with Lookup Tables and Diffusion Priors
Yunlong Lin, Zhenqi Fu, Kairun Wen +7
Low-light image enhancement (LIE) aims at precisely and efficiently recovering an image degraded in poor illumination environments. Recent advanced LIE techniques are using deep ne…
Teaching Tailored to Talent: Adverse Weather Restoration via Prompt Pool and Depth-Anything Constraint
Sixiang Chen, Tian Ye, Kai Zhang +3
Recent advancements in adverse weather restoration have shown potential, yet the unpredictable and varied combinations of weather degradations in the real world pose significant ch…
Dual-former: Hybrid Self-attention Transformer for Efficient Image Restoration
Sixiang Chen, Tian Ye, Yun Liu +1
Recently, image restoration transformers have achieved comparable performance with previous state-of-the-art CNNs. However, how to efficiently leverage such architectures remains a…
Underwater Light Field Retention : Neural Rendering for Underwater Imaging
Tian Ye, Sixiang Chen, Yun Liu +3
Underwater Image Rendering aims to generate a true-tolife underwater image from a given clean one, which could be applied to various practical applications such as underwater image…
Towards Efficient Single Image Dehazing and Desnowing
Tian Ye, Sixiang Chen, Yun Liu +2
Removing adverse weather conditions like rain, fog, and snow from images is a challenging problem. Although the current recovery algorithms targeting a specific condition have made…
Mutual Learning for Domain Adaptation: Self-distillation Image Dehazing Network with Sample-cycle
Tian Ye, Yun Liu, Yunchen Zhang +2
Deep learning-based methods have made significant achievements for image dehazing. However, most of existing dehazing networks are concentrated on training models using simulated h…