Unified Image Restoration
3 papers with code • 0 benchmarks • 0 datasets
Using a single model to restore inputs with different degradation types.
Benchmarks
These leaderboards are used to track progress in Unified Image Restoration
Most implemented papers
Photo-Realistic Image Restoration in the Wild with Controlled Vision-Language Models
Though diffusion models have been successfully applied to various image restoration (IR) tasks, their performance is sensitive to the choice of training datasets.
Controlling Vision-Language Models for Multi-Task Image Restoration
In this paper, we present a degradation-aware vision-language model (DA-CLIP) to better transfer pretrained vision-language models to low-level vision tasks as a multi-task framework for image restoration.
CRNet: A Detail-Preserving Network for Unified Image Restoration and Enhancement Task
In real-world scenarios, images captured often suffer from blurring, noise, and other forms of image degradation, and due to sensor limitations, people usually can only obtain low dynamic range images.
