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Perceptual Image Restoration with High-Quality Priori and Degradation Learning
Perceptual image restoration seeks for high-fidelity images that most likely degrade to given images. -
RESIDE-β Dataset
The dataset used for testing the proposed network. -
Restoring Images with Unknown Degradation Factors
The proposed network is used for image restoration with unknown degradation factors. -
SnowCityScapes
The SnowCityScapes dataset is a real-world dataset for single image desnowing. -
Poisson Inverse Problems
The dataset used in this paper is Poisson inverse problems involving the Poisson data-fidelity term f introduced in (2). -
CU-Mamba: Selective State Space Models with Channel Learning for Image Restor...
The CU-Mamba model is used for image restoration, and the authors tested it on the SIDD and DND datasets. -
Open Turbulent Image Set (OTIS)
The Open Turbulent Image Set (OTIS) dataset contains images of turbulent scenes. -
TMT Dataset
The TMT dataset consists of static and dynamic parts. The static part is synthesized using the place dataset [58] for static scenes. The dynamic part is generated using the... -
Real Image Restoration and Enhancement
Real-world image restoration and enhancement -
Generative Diffusion Prior
The dataset used in the Generative Diffusion Prior for unified image restoration and enhancement. -
Laser dazzle protection
A dataset for image restoration in phase mask based anti-dazzle imaging systems. -
SandPascal VOC++
SandPascal VOC++ dataset is a synthetic dataset for sand dust image restoration tasks, containing three forms of sand.