As a vital image enhancement technology, infrared and visible image fusion aims to
generate high-quality fused images with salient targets and abundant texture in extreme …

As a critical preprocessing technique, low-illumination image enhancement has a wide
range of practical applications. It aims to improve the visual perception of a given image …

Collecting paired training data is difficult in practice, but the unpaired samples broadly exist.
Current approaches aim at generating synthesized training data from unpaired samples by …

With the rapid development of AI hardware accelerators, applying deep learning-based
algorithms to solve various low-level vision tasks on mobile devices has gradually become …

Exposure errors in an image cause a degradation in the contrast and low visibility in the
content. In this paper, we address this problem and propose an end-to-end exposure …

Inadequate illumination often causes severe image degradation, such as noise and artifacts.
These types of images do not meet the requirements of advanced visual tasks, so low-light …

Photos taken under nighttime or backlit conditions often suffer from complex and
unpredictable degradation, such as low visibility, messy noise, and distorted color. Previous …

Most existing infrared image enhancement algorithms focus on detail and contrast
enhancement of ordinary infrared images, and when applied to low-light infrared images …

Nighttime environments with sub-optimal lighting conditions significantly degrade the quality
of captured images. Even though many notable state-of-the-art methods had been proposed …

We present a new additive image factorization technique that treats images to be composed
of multiple latent specular components which can be simply estimated recursively by …