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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>BibTex</title>
<style>
html,body{margin:0;padding:0}
.anchor{display:block}
.placeholder{height:800px;padding:0}
</style>
</head>
<body>
<a id="liang2024movideo" name="liang2024movideo">
@inproceedings{liang2024movideo,</br>
title={MoVideo: Motion-Aware Video Generation with Diffusion Models},</br>
author={Liang, Jingyun and Fan, Yuchen and Zhang, Kai and Timofte, Radu and Van Gool, Luc and Ranjan, Rakesh},</br>
journal={ECCV},</br>
year={2024}</br>
}</br>
</a>
<a id="zhang2023practical" name="zhang2023practical">
@article{zhang2023practical,</br>
title={Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis},</br>
author={Zhang, Kai and Li, Yawei and Liang, Jingyun and Cao, Jiezhang and Zhang, Yulun and Tang, Hao and Fan, Deng-Ping and Timofte, Radu and Van Gool, Luc},</br>
journal={Machine Intelligence Research},</br>
volume={20},</br>
number={6},</br>
pages={822--836},</br>
year={2023}</br>
}</br>
</a>
<a id="liang2022recurrent" name="liang2022recurrent">
@inproceedings{liang2022recurrent,</br>
title={Recurrent Video Restoration Transformer with Guided Deformable Attention},</br>
author={Liang, Jingyun and Fan, Yuchen and Xiang, Xiaoyu and Ranjan, Rakesh and Ilg, Eddy and Green, Simon and Cao, Jiezhang and Zhang, Kai and Timofte, Radu and Van Gool, Luc},</br>
journal={NeurIPS},</br>
year={2022}</br>
}</br>
</a>
<a id="cao2022towards" name="cao2022towards">
@inproceedings{cao2022towards,</br>
title={Towards Interpretable Video Super-Resolution via Alternating Optimization},</br>
author={Cao, Jiezhang and Liang, Jingyun and Zhang, Kai and Wang, Wenguan and Wang, Qin and Zhang, Yulun and Tang, Hao and Van Gool, Luc},</br>
booktitle={European conference on computer vision},</br>
year={2022}</br>
}</br>
</a>
<a id="zhang2022deep" name="zhang2022deep">
@incollection{zhang2022deep,</br>
title = {Deep plug-and-play and deep unfolding methods for image restoration},</br>
editor = {E.R. Davies and Matthew A. Turk},</br>
author = {Kai Zhang and Radu Timofte},</br>
booktitle = {Advanced Methods and Deep Learning in Computer Vision},</br>
publisher = {Academic Press},</br>
pages = {481-509},</br>
year = {2022}</br>
}</br>
</a>
<a id="liang2021swinir" name="liang2021swinir">
@inproceedings{liang2021swinir,</br>
title={SwinIR: Image Restoration Using Swin Transformer},</br>
author={Liang, Jingyun and Cao, Jiezhang and Sun, Guolei and Zhang, Kai and Van Gool, Luc and Timofte, Radu},</br>
booktitle={IEEE International Conference on Computer Vision Workshops},</br>
pages={1833--1844},</br>
year={2021}</br>
}</br>
</a>
<a id="zhang2021designing" name="zhang2021designing">
@inproceedings{zhang2021designing,</br>
title={Designing a Practical Degradation Model for Deep Blind Image Super-Resolution},</br>
author={Zhang, Kai and Liang, Jingyun and Van Gool, Luc and Timofte, Radu},</br>
booktitle={IEEE International Conference on Computer Vision},</br>
pages={4791--4800},</br>
year={2021}</br>
}</br>
</a>
<a id="liang2021mutual" name="liang2021mutual">
@inproceedings{liang2021mutual,</br>
title={Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution},</br>
author={Liang, Jingyun and Sun, Guolei and Zhang, Kai and Van Gool, Luc and Timofte, Radu},</br>
booktitle={IEEE International Conference on Computer Vision},</br>
pages={4096--4105},</br>
year={2021}</br>
}</br>
</a>
<a id="jiang2021towards" name="jiang2021towards">
@inproceedings{jiang2021towards,</br>
title={Towards Flexible Blind {JPEG} Artifacts Removal},</br>
author={Jiang, Jiaxi and Zhang, Kai and Timofte, Radu},</br>
booktitle={IEEE International Conference on Computer Vision},</br>
pages={4997--5006},</br>
year={2021}</br>
}</br>
</a>
<a id="liang2021hierarchical" name="liang2021hierarchical">
@inproceedings{liang2021hierarchical,</br>
title={Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling},</br>
author={Liang, Jingyun and Lugmayr, Andreas and Zhang, Kai and Danelljan, Martin and Van Gool, Luc and Timofte, Radu},</br>
booktitle={IEEE International Conference on Computer Vision},</br>
pages={4076--4085},</br>
year={2021}</br>
}</br>
</a>
<a id="liang2021flow" name="liang2021flow">
@inproceedings{liang2021flow,</br>
title={Flow-based Kernel Prior with Application to Blind Super-Resolution},</br>
author={Liang, Jingyun and Zhang, Kai and Gu, Shuhang and Van Gool, Luc and Timofte, Radu},</br>
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},</br>
pages={10601--10610},</br>
year={2021}</br>
}</br>
</a>
<a id="zhang2020plug" name="zhang2020plug">
@article{zhang2020plug,</br>
title={Plug-and-Play Image Restoration with Deep Denoiser Prior},</br>
author={Zhang, Kai and Li, Yawei and Zuo, Wangmeng and Zhang, Lei and Van Gool, Luc and Timofte, Radu},</br>
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},</br>
volume={44},</br>
number={10},</br>
pages={6360-6376},</br>
year={2022}</br>
}</br>
</a>
<a id="zhang2020aim" name="zhang2020aim">
@inproceedings{zhang2020aim,</br>
title={AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results},</br>
author={Kai Zhang and Martin Danelljan and Yawei Li and Radu Timofte and others},</br>
booktitle={European Conference on Computer Vision Workshops},</br>
year={2020}</br>
}</br>
</a>
<a id="zhang2020deep" name="zhang2020deep">
@inproceedings{zhang2020deep, % USRNet</br>
title={Deep unfolding network for image super-resolution},</br>
author={Zhang, Kai and Van Gool, Luc and Timofte, Radu},</br>
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},</br>
pages={3217--3226},</br>
year={2020}</br>
}</br>
</a>
<a id="ren2019neural" name="ren2019neural" class="anchor">
@inproceedings{ren2019neural,</br>
title={Neural blind deconvolution using deep priors},</br>
author={Ren, Dongwei and Zhang, Kai and Wang, Qilong and Hu, Qinghua and Zuo, Wangmeng},</br>
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},</br>
pages={3341--3350},</br>
year={2020}</br>
}</br>
</a>
<a id="zhang2020ntire" name="zhang2020ntire" class="anchor">
@inproceedings{zhang2020ntire, </br>
title={NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results},</br>
author={Kai Zhang and Shuhang Gu and Radu Timofte and others},</br>
booktitle={IEEE International Conference on Computer Vision and Pattern Recognition Workshops},</br>
year={2020}</br>
}</br>
</a>
<a id="zhang2019aim" name="zhang2019aim" class="anchor">
@inproceedings{zhang2019aim, % AIM 2019</br>
title={AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results},</br>
author={Kai Zhang and Shuhang Gu and Radu Timofte and others},</br>
booktitle={IEEE International Conference on Computer Vision Workshops},</br>
year={2019}</br>
}</br>
</a>
<a id="zhang2019deep" name="zhang2019deep" class="anchor">
@inproceedings{zhang2019deep, % DPSR</br>
title={Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels},</br>
author={Zhang, Kai and Zuo, Wangmeng and Zhang, Lei},</br>
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},</br>
pages={1671--1681},</br>
year={2019}</br>
}</br>
</a>
<a id="zhang2018learning" name="zhang2018learning" class="anchor">
@inproceedings{zhang2018learning, % SRMD</br>
title={Learning a single convolutional super-resolution network for multiple degradations},</br>
author={Zhang, Kai and Zuo, Wangmeng and Zhang, Lei},</br>
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},</br>
pages={3262--3271},</br>
year={2018}</br>
}</br>
</a>
<a id="zhang2017learning" name="zhang2017learning" class="anchor">
@inproceedings{zhang2017learning, % IRCNN</br>
title={Learning deep CNN denoiser prior for image restoration},</br>
author={Zhang, Kai and Zuo, Wangmeng and Gu, Shuhang and Zhang, Lei},</br>
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},</br>
pages={3929--3938},</br>
year={2017}</br>
}</br>
</a>
<a id="zhang2018ffdnet" name="zhang2018ffdnet" class="anchor">
@article{zhang2018ffdnet, % FFDNet, FDnCNN</br>
title={{FFDNet}: Toward a fast and flexible solution for {CNN}-based image denoising},</br>
author={Zhang, Kai and Zuo, Wangmeng and Zhang, Lei},</br>
journal={IEEE Transactions on Image Processing},</br>
volume={27},</br>
number={9},</br>
pages={4608--4622},</br>
year={2018}</br>
}</br>
</a>
<a id="zhang2017beyond" name="zhang2017beyond" class="anchor">
@article{zhang2017beyond, %DnCNN</br>
title={Beyond a {Gaussian} denoiser: Residual learning of deep {CNN} for image denoising},</br>
author={Zhang, Kai and Zuo, Wangmeng and Chen, Yunjin and Meng, Deyu and Zhang, Lei},</br>
journal={IEEE Transactions on Image Processing},</br>
year={2017},</br>
volume={26}, </br>
number={7}, </br>
pages={3142-3155}, </br>
}</br>
</a>
<a id="ma2017end" name="ma2017end" class="anchor">
@article{ma2017end,</br>
title={End-to-end blind image quality assessment using deep neural networks},</br>
author={Ma, Kede and Liu, Wentao and Zhang, Kai and Duanmu, Zhengfang and Wang, Zhou and Zuo, Wangmeng},</br>
journal={IEEE Transactions on Image Processing},</br>
volume={27},</br>
number={3},</br>
pages={1202--1213},</br>
year={2017}</br>
}</br>
</a>
<a id="guo2019toward" name="guo2019toward" class="anchor">
@inproceedings{guo2019toward,</br>
title={Toward convolutional blind denoising of real photographs},</br>
author={Guo, Shi and Yan, Zifei and Zhang, Kai and Zuo, Wangmeng and Zhang, Lei},</br>
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},</br>
pages={1712--1722},</br>
year={2019}</br>
}</br>
</a>
<a id="zuo2018convolutional" name="zuo2018convolutional" class="anchor">
@Inbook{zuo2018convolutional,</br>
author={Zuo, Wangmeng and Zhang, Kai and Zhang, Lei},</br>
editor={Bertalm{\'i}o, Marcelo},</br>
title={Convolutional Neural Networks for Image Denoising and Restoration},</br>
bookTitle={Denoising of Photographic Images and Video: Fundamentals, Open Challenges and New Trends},</br>
year={2018},</br>
publisher={Springer International Publishing},</br>
address={Cham},</br>
pages={93--123},</br>
isbn={978-3-319-96029-6},</br>
doi={10.1007/978-3-319-96029-6_4},</br>
url={https://doi.org/10.1007/978-3-319-96029-6_4}</br>
}</br>
</a>
<a id="zhang2015joint" name="zhang2015joint" class="anchor">
@article{zhang2015joint,</br>
title={Joint learning of multiple regressors for single image super-resolution},</br>
author={Zhang, Kai and Wang, Baoquan and Zuo, Wangmeng and Zhang, Hongzhi and Zhang, Lei},</br>
journal={IEEE Signal processing letters},</br>
volume={23},</br>
number={1},</br>
pages={102--106},</br>
year={2015}</br>
}</br>
</a>
<a id="zhang2015revisiting" name="zhang2015revisiting" class="anchor">
@inproceedings{zhang2015revisiting,</br>
title={Revisiting single image super-resolution under internet environment: blur kernels and reconstruction algorithms},</br>
author={Zhang, Kai and Zhou, Xiaoyu and Zhang, Hongzhi and Zuo, Wangmeng},</br>
booktitle={Pacific Rim Conference on Multimedia},</br>
pages={677--687},</br>
year={2015}</br>
}</br>
</a>
</body>
</html>