222 citations · 555 across the 35 of their papers we have counts for
8 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…
Learning Task-Oriented Flows to Mutually Guide Feature Alignment in Synthesized and Real Video Denoising
Jiezhang Cao, Qin Wang, Jingyun Liang +4
Video denoising aims at removing noise from videos to recover clean ones. Some existing works show that optical flow can help the denoising by exploiting the additional spatial-tem…
Towards Interpretable Video Super-Resolution via Alternating Optimization
Jiezhang Cao, Jingyun Liang, Kai Zhang +5
In this paper, we study a practical space-time video super-resolution (STVSR) problem which aims at generating a high-framerate high-resolution sharp video from a low-framerate low…
Towards Lightweight Super-Resolution with Dual Regression Learning
Yong Guo, Mingkui Tan, Zeshuai Deng +5
Deep neural networks have exhibited remarkable performance in image super-resolution (SR) tasks by learning a mapping from low-resolution (LR) images to high-resolution (HR) images…
Recurrent Video Restoration Transformer with Guided Deformable Attention
Jingyun Liang, Yuchen Fan, Xiaoyu Xiang +7
Video restoration aims at restoring multiple high-quality frames from multiple low-quality frames. Existing video restoration methods generally fall into two extreme cases, i.e., t…
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…