Video super-resolution (VSR) approaches tend to have more components than the image
counterparts as they need to exploit the additional temporal dimension. Complex designs …

Image Super-Resolution (SR) is an important class of image processing techniqueso
enhance the resolution of images and videos in computer vision. Recent years have …

Transformer-based methods have exhibited remarkable potential in single image super-
resolution (SISR) by effectively extracting long-range dependencies. However, most of the …

This book provides a structured treatment of the key principles and techniques for enabling
efficient processing of deep neural networks (DNNs). DNNs are currently widely used for …

Live video accounts for a significant volume of today's Internet video. Despite a large
number of efforts to enhance user quality of experience (QoE) both at the ingest and …

The demand for mobile video streaming has experienced tremendous growth over the last
decade. However, existing methods of video delivery fall short of delivering high-quality …

High-definition live streaming has experienced tremendous growth. However, the video
quality of live video is often limited by the streamer's uplink bandwidth. Recently, neural …

The omnidirectional images (ODIs) are usually at low-resolution, due to the constraints of
collection, storage and transmission. The traditional two-dimensional (2D) image super …

Video compression is a critical component of Internet video delivery. Recent work has
shown that deep learning techniques can rival or outperform human-designed algorithms …

Hardware support for deep convolutional neural networks (CNNs) is critical to advanced
computer vision in mobile and embedded devices. Current designs, however, accelerate …