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…
Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution
Jingyun Liang, Guolei Sun, Kai Zhang +2
Existing blind image super-resolution (SR) methods mostly assume blur kernels are spatially invariant across the whole image. However, such an assumption is rarely applicable for r…
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…
Video Super-Resolution Transformer
Jiezhang Cao, Yawei Li, Kai Zhang +1
Video super-resolution (VSR), with the aim to restore a high-resolution video from its corresponding low-resolution version, is a spatial-temporal sequence prediction problem. Rece…
LocalViT: Analyzing Locality in Vision Transformers
Yawei Li, Kai Zhang, Jiezhang Cao +4
The aim of this paper is to study the influence of locality mechanisms in vision transformers. Transformers originated from machine translation and are particularly good at modelli…
Flow-based Kernel Prior with Application to Blind Super-Resolution
Jingyun Liang, Kai Zhang, Shuhang Gu +2
Kernel estimation is generally one of the key problems for blind image super-resolution (SR). Recently, Double-DIP proposes to model the kernel via a network architecture prior, wh…
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…