Video super-resolution based on deep learning: a comprehensive survey
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 …
ones. Recently, the VSR methods based on deep neural networks have made great …
NTIRE 2022 challenge on super-resolution and quality enhancement of compressed video: Dataset, methods and results
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 …
Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset …
Maniqa: Multi-dimension attention network for no-reference image quality assessment
Abstract No-Reference Image Quality Assessment (NR-IQA) aims to assess the perceptual
quality of images in accordance with human subjective perception. Unfortunately, existing …
quality of images in accordance with human subjective perception. Unfortunately, existing …
Vrt: A video restoration transformer
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 …
single image restoration, video restoration generally requires to utilize temporal information …
Recurrent video restoration transformer with guided deformable attention
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 …
frames. Existing video restoration methods generally fall into two extreme cases, ie, they …
Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better
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 …
deblurring, named DeblurGAN-V2, which considerably boosts state-of-the-art deblurring …
Edvr: Video restoration with enhanced deformable convolutional networks
Video restoration tasks, including super-resolution, deblurring, etc, are drawing increasing
attention in the computer vision community. A challenging benchmark named REDS is …
attention in the computer vision community. A challenging benchmark named REDS is …
Deep learning for image super-resolution: A survey
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 …
enhance the resolution of images and videos in computer vision. Recent years have …
Tdan: Temporally-deformable alignment network for video super-resolution
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 …
frame from both its corresponding low-resolution (LR) frame (reference frame) and multiple …
Benchmarking single-image dehazing and beyond
We present a comprehensive study and evaluation of existing single-image dehazing
algorithms, using a new large-scale benchmark consisting of both synthetic and real-world …
algorithms, using a new large-scale benchmark consisting of both synthetic and real-world …