Abstract Automated Driving Systems (ADS) open up a new domain for the automotive
industry and offer new possibilities for future transportation with higher efficiency and …

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 …

We propose a novel unsupervised backlit image enhancement method, abbreviated as CLIP-
LIT, by exploring the potential of Contrastive Language-Image Pre-Training (CLIP) for pixel …

Night images suffer not only from low light, but also from uneven distributions of light. Most
existing night visibility enhancement methods focus mainly on enhancing low-light regions …

Images captured under incorrect exposures unavoidably suffer from mixed degradations of
lightness and structures. Most existing deep learning-based exposure correction methods …

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 …

Challenging illumination conditions (low-light, under-exposure and over-exposure) in the
real world not only cast an unpleasant visual appearance but also taint the computer vision …

Exposure correction task aims to correct the underexposure and its adverse overexposure
images to the normal exposure in a single network. As well recognized, the optimization flow …

Existing image enhancement methods are typically designed to address either the over-or
under-exposure problem in the input image. When the illumination of the input image …

Lightness adaptation is vital to the success of image processing to avoid unexpected visual
deterioration, which covers multiple aspects, eg, low-light image enhancement, image …