As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …

Deep learning has been overwhelmingly successful in computer vision (CV), natural
language processing, and video/speech recognition. In this paper, our focus is on CV. We …

Image inpainting has been widely exploited in the field of computer vision and image
processing. The main purpose of image inpainting is to produce visually plausible structure …

Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …

Images captured under low-light conditions often suffer from (partially) poor visibility.
Besides unsatisfactory lightings, multiple types of degradation, such as noise and color …

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 …

When training or evaluating deep learning models, two essential parts are picking the
proper loss function and deciding on performance metrics. In this paper, we provide a …

A range of alternative approaches to traditional digital hardware have been explored for the
implementation of artificial neural networks, including optical neural networks and diffractive …

Images captured under low-light conditions often suffer from (partially) poor visibility.
Besides unsatisfactory lightings, multiple types of degradations, such as noise and color …

In last few years, supervised deep learning has emerged as one powerful tool for image
denoising, which trains a denoising network over an external dataset of noisy/clean image …