285 citations · 838 across the 56 of their papers we have counts for
6 papers · 1 filter
CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolution
Jiezhang Cao, Qin Wang, Yongqin Xian +7
Learning continuous image representations is recently gaining popularity for image super-resolution (SR) because of its ability to reconstruct high-resolution images with arbitrary…
Reference-based Image Super-Resolution with Deformable Attention Transformer
Jiezhang Cao, Jingyun Liang, Kai Zhang +4
Reference-based image super-resolution (RefSR) aims to exploit auxiliary reference (Ref) images to super-resolve low-resolution (LR) images. Recently, RefSR has been attracting gre…
Revisiting Random Channel Pruning for Neural Network Compression
Yawei Li, Kamil Adamczewski, Wen Li +3
Channel (or 3D filter) pruning serves as an effective way to accelerate the inference of neural networks. There has been a flurry of algorithms that try to solve this practical pro…
NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results
Yawei Li, Kai Zhang, Radu Timofte +108
This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-reso…
Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis
Kai Zhang, Yawei Li, Jingyun Liang +6
While recent years have witnessed a dramatic upsurge of exploiting deep neural networks toward solving image denoising, existing methods mostly rely on simple noise assumptions, su…
VRT: A Video Restoration Transformer
Jingyun Liang, Jiezhang Cao, Yuchen Fan +5
Video restoration (e.g., video super-resolution) aims to restore high-quality frames from low-quality frames. Different from single image restoration, video restoration generally r…