This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting
the proposed solutions and results. The aim of this challenge is to discover an effective …

This article reviews the deep learning methods for computed tomography image denoising
and deblurring separately and simultaneously. Then, we discuss promising directions in this …

Restoring a high-quality image from a noisy version poses a significant challenge in
computer vision, particularly in today's context where high-resolution and large-sized …

Neural networks as a core information processing technology in machine learning and
artificial intelligence demand substantial computational resources to deal with the extensive …

The advancement of digitization and automation in Low Altitude Intelligent Networking
(LAIN) is constrained by limited computational resources and the absence of a dedicated …

The fusion of visible and infrared images aims to produce high-quality fusion images with
rich textures and salient target information. Existing methods lack interactivity and flexibility …

This paper introduces a novel approach for high-quality deepfake detection called Localized
Artifact Attention Network (LAA-Net). Existing methods for high-quality deepfake detection …

Supervised training of deep neural networks on pairs of clean image and noisy
measurement achieves state-of-the-art performance for many image reconstruction tasks …

Removing noise from images aka image denoising can be a very challenging task since the
type and amount of noise can greatly vary for each image due to many factors including a …

Image reconstruction from incomplete measurements is a basic task in medical imaging.
While supervised deep learning proves to be a powerful tool for image reconstruction, it …