Video super-resolution (VSR) is reconstructing high-resolution videos from low resolution
ones. Recently, the VSR methods based on deep neural networks have made great …

This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality
Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset …

Abstract No-Reference Image Quality Assessment (NR-IQA) aims to assess the perceptual
quality of images in accordance with human subjective perception. Unfortunately, existing …

Video restoration aims to restore high-quality frames from low-quality frames. Different from
single image restoration, video restoration generally requires to utilize temporal information …

Video restoration aims at restoring multiple high-quality frames from multiple low-quality
frames. Existing video restoration methods generally fall into two extreme cases, ie, they …

We present a new end-to-end generative adversarial network (GAN) for single image motion
deblurring, named DeblurGAN-V2, which considerably boosts state-of-the-art deblurring …

Video restoration tasks, including super-resolution, deblurring, etc, are drawing increasing
attention in the computer vision community. A challenging benchmark named REDS is …

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 …

Video super-resolution (VSR) aims to restore a photo-realistic high-resolution (HR) video
frame from both its corresponding low-resolution (LR) frame (reference frame) and multiple …

Most video super-resolution methods super-resolve a single reference frame with the help of
neighboring frames in a temporal sliding window. They are less efficient compared to the …