Multi-modality image fusion and segmentation play a vital role in autonomous driving and
robotic operation. Early efforts focus on boosting the performance for only one task, eg …

Nighttime image dehazing is a challenging task due to the presence of multiple types of
adverse degrading effects including glow, haze, blur, noise, color distortion, and so on …

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 …

We present AutoDIR, an innovative all-in-one image restoration system incorporating latent
diffusion. AutoDIR excels in its ability to automatically identify and restore images suffering …

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

In this paper we introduce a new perspective for improving image restoration by removing
degradation in the textual representations of a given degraded image. Intuitively restoration …

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 …

Traditional single-task image restoration methods excel in handling specific degradation
types but struggle with multiple degradations. To address this limitation, we propose …

Existing methods have demonstrated effective performance on a single degradation type. In
practical applications, however, the degradation is often unknown, and the mismatch …

Fundus image quality serves a crucial asset for medical diagnosis and applications.
However, such images often suffer degradation during image acquisition where multiple …