Image restoration involves recovering a high-quality clean image from its degraded version.
Deep learning-based methods have significantly improved image restoration performance …

Pre-training has marked numerous state of the arts in high-level computer vision, while few
attempts have ever been made to investigate how pre-training acts in image processing …

Image restoration is a fundamental problem that involves recovering a high-quality clean
image from its degraded observation. All-In-One image restoration models can effectively …

Learning to leverage the relationship among diverse image restoration tasks is quite
beneficial for unraveling the intrinsic ingredients behind the degradation. Recent years have …

The Vision Transformer (ViT) architecture has been remarkably successful in image
restoration. For a while, Convolutional Neural Networks (CNN) predominated in most …

Image processing, including image restoration, image enhancement, etc., involves
generating a high-quality clean image from a degraded input. Deep learning-based …

Despite substantial progress all-in-one image restoration (IR) grapples with persistent
challenges in handling intricate real-world degradations. This paper introduces MPerceiver …

Self-supervised pretraining has achieved remarkable success in high-level vision, but its
application in low-level vision remains ambiguous and not well-established. What is the …

Despite the significant progress made by deep models in various image restoration tasks,
existing image restoration networks still face challenges in terms of task generality. An …

Image restoration (IR) refers to the process of improving visual quality of images while
removing degradation, such as noise, blur, weather effects, and so on. Traditional IR …