9.2k citations · 13.2k across the 30 of their papers we have counts for
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Towards Flexible Blind JPEG Artifacts Removal
Jiaxi Jiang, Kai Zhang, Radu Timofte
Training a single deep blind model to handle different quality factors for JPEG image artifacts removal has been attracting considerable attention due to its convenience for practi…
SwinIR: Image Restoration Using Swin Transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun +3
Image restoration is a long-standing low-level vision problem that aims to restore high-quality images from low-quality images (e.g., downscaled, noisy and compressed images). Whil…
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling
Jingyun Liang, Andreas Lugmayr, Kai Zhang +3
Normalizing flows have recently demonstrated promising results for low-level vision tasks. For image super-resolution (SR), it learns to predict diverse photo-realistic high-resolu…
Designing a Practical Degradation Model for Deep Blind Image Super-Resolution
Kai Zhang, Jingyun Liang, Luc Van Gool +1
It is widely acknowledged that single image super-resolution (SISR) methods would not perform well if the assumed degradation model deviates from those in real images. Although sev…
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
Kai Zhang, Martin Danelljan, Yawei Li +75
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an in…
Plug-and-Play Image Restoration with Deep Denoiser Prior
Kai Zhang, Yawei Li, Wangmeng Zuo +3
Recent works on plug-and-play image restoration have shown that a denoiser can implicitly serve as the image prior for model-based methods to solve many inverse problems. Such a pr…
Learning Context-Based Non-local Entropy Modeling for Image Compression
Mu Li, Kai Zhang, Wangmeng Zuo +2
The entropy of the codes usually serves as the rate loss in the recent learned lossy image compression methods. Precise estimation of the probabilistic distribution of the codes pl…
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte +60
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input im…
Deep Unfolding Network for Image Super-Resolution
Kai Zhang, Luc Van Gool, Radu Timofte
Learning-based single image super-resolution (SISR) methods are continuously showing superior effectiveness and efficiency over traditional model-based methods, largely due to the…