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 …

Image deblurring is a classic problem in low-level computer vision with the aim to recover a
sharp image from a blurred input image. Advances in deep learning have led to significant …

Dynamic neural network is an emerging research topic in deep learning. Compared to static
models which have fixed computational graphs and parameters at the inference stage …

Low-light image enhancement (LLIE) aims at improving the perception or interpretability of
an image captured in an environment with poor illumination. Recent advances in this area …

Abstract Neural Radiance Field (NeRF) has gained considerable attention recently for 3D
scene reconstruction and novel view synthesis due to its remarkable synthesis quality …

Video anomaly detection (VAD) is a significant computer vision problem. Existing deep
neural network (DNN) based VAD methods mostly follow the route of frame reconstruction or …

In single image deblurring, the``coarse-to-fine''scheme, ie gradually restoring the sharp
image on different resolutions in a pyramid, is very successful in both traditional optimization …

This paper introduces a novel large dataset for video deblurring, video super-resolution and
studies the state-of-the-art as emerged from the NTIRE 2019 video restoration challenges …

Recent advances in video super-resolution have shown that convolutional neural networks
combined with motion compensation are able to merge information from multiple low …

Blind deconvolution is a classical yet challenging low-level vision problem with many real-
world applications. Traditional maximum a posterior (MAP) based methods rely heavily on …