2 papers
cs.CV2025
Prompt to Restore, Restore to Prompt: Cyclic Prompting for Universal Adverse Weather Removal
Rongxin Liao, Feng Li, Yanyan Wei +4
Universal adverse weather removal (UAWR) seeks to address various weather degradations within a unified framework. Recent methods are inspired by prompt learning using pre-trained…
cs.CV2025
Learning Dual Transformers for All-In-One Image Restoration from a Frequency Perspective
Jie Chu, Tong Su, Pei Liu +4
This work aims to tackle the all-in-one image restoration task, which seeks to handle multiple types of degradation with a single model. The primary challenge is to extract degrada…