This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …

Images acquired in poor weather conditions (haze, fog, smog, mist, etc.) are often severely
degraded. In the atmosphere, there exists two types of particles: dry particles (dust, smoke …

Image dehazing is a representative low-level vision task that estimates latent haze-free
images from hazy images. In recent years, convolutional neural network-based methods …

Recent progress on Transformers and multi-layer perceptron (MLP) models provide new
network architectural designs for computer vision tasks. Although these models proved to be …

Infrared and visible image fusion aims to synthesize a single fused image that not only
contains salient targets and abundant texture details but also facilitates high-level vision …

Considering the ill-posed nature, contrastive regularization has been developed for single
image dehazing, introducing the information from negative images as a lower bound …

Global modeling-based image restoration frameworks have become popular. However, they
often require a high memory footprint and do not consider task-specific degradation. Our …

In this paper, we study a challenging problem in image restoration, namely, how to develop
an all-in-one method that could recover images from a variety of unknown corruption types …

To overcome the overfitting issue of dehazing models trained on synthetic hazy-clean image
pairs, many recent methods attempted to improve models' generalization ability by training …

Single image dehazing is a challenging ill-posed problem due to the severe information
degeneration. However, existing deep learning based dehazing methods only adopt clear …