Low-light image enhancement is a notoriously challenging problem. Enhancement of low-
light images is intended to increase contrast, adjust the tone, suppress noise, and produce …

Synthetic realities are digital creations or augmentations that are contextually generated
through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data …

As the quality of optical sensors improves, there is a need for processing large-scale
images. In particular, the ability of devices to capture ultra-high definition (UHD) images and …

We introduce a novel method using a new generative model that automatically learns
effective representations of the target and background appearance to detect, segment and …

Low-light image enhancement (LLIE) investigates how to improve illumination and produce
normal-light images. The majority of existing methods improve low-light images via a global …

This paper proposes a new framework for low-light image enhancement by simultaneously
conducting the appearance as well as structure modeling. It employs the structural feature to …

Recent deep learning methods have achieved promising results in image shadow removal.
However, their restored images still suffer from unsatisfactory boundary artifacts, due to the …

Previous raw image-based low-light image enhancement methods predominantly relied on
feed-forward neural networks to learn deterministic mappings from low-light to normally …

Shadow removal, which aims to restore the background in the shadow regions, is
challenging due to the highly ill-posed nature. Most existing deep learning-based methods …

Recovering noise-covered details from low-light images is challenging, and the results given
by previous methods leave room for improvement. Recent diffusion models show realistic …