With the prosperity of Industry 4.0, numerous emerging industries continue to gain popularity
and their market scales are expanding ceaselessly. The Internet of Vehicles (IoV), one of the …

Learning-based post-processing methods generally produce neural models that are
statistically optimal on their training datasets. These models, however, neglect intrinsic …

Block-based video codecs such as Versatile Video Coding (VVC)/H. 266, High Efficiency
Video Coding (HEVC)/H. 265, Advanced Video Coding (AVC)/H. 264 etc. inherently …

This article proposes a reconfigurable framework for neural network based video in-loop
filtering to guide large-scale models for content-aware processing. Specifically, the …

This paper provides a survey of the latest developments in visual signal coding and
processing with generative models. Specifically, our focus is on presenting the advancement …

Screen content has become one of the prominent mediums in the increasingly connected
world. With the prevalence of remote collaboration and communication such as virtual …

Deep neural networks have achieved remarkable success in HEVC compressed video
quality enhancement. However, most existing multiframe-based methods either deliver …

This paper presents a hybrid video compression framework, aiming at providing a
demonstration of applying deep learning-based approaches beyond conventional coding …

The past decade has witnessed the huge success of deep learning in well-known artificial
intelligence applications such as face recognition, autonomous driving, and large language …

In this article, we propose an efficient reference-based deep in-loop filtering method for
video coding. Existing reference-based in-loop filters often face challenges in improving …