Kai Zhang

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Wangmeng ZuoSchool of Computer Science and Technology, Harbin Institute of TechnologyVerified email at hit.edu.cn
Radu TimofteUniversity of Würzburg & ETH ZurichVerified email at uni-wuerzburg.de
Luc Van Goolprofessor computer vision ETH Zurich,KU Leuven,INSAIT,Head Toyota Lab TRACE @KUL&ETHVerified email at ethz.ch
Lei ZhangChair Professor, Dept. of Computing, The Hong Kong Polytechnic UniversityVerified email at comp.polyu.edu.hk
Jingyun LiangPhD student, ETH ZurichVerified email at vision.ee.ethz.ch
Jiezhang CaoPhD Student, ETH ZürichVerified email at ee.ethz.ch
Yawei LiETH ZurichVerified email at vision.ee.ethz.ch
Yunjin CHENAlibaba CloudVerified email at alibaba-inc.com
Deyu MengProfessor, Xi'an Jiaotong UniversityVerified email at mail.xjtu.edu.cn
Hongzhi ZhangAssociate Professor of Computer Science and Technology, Harbin Institute of TechnologyVerified email at hit.edu.cn
Qinghua HuProfessor of Computer Science, Tianjin UniversityVerified email at tju.edu.cn
Kede MaAssistant Professor of Computer Science, City University of Hong KongVerified email at cityu.edu.hk
Zhou WangProfessor, Electrical and Computer Engineering, University of WaterlooVerified email at uwaterloo.ca
Dongwei RenHarbin Institute of TechnologyVerified email at hit.edu.cn
Hao TangETH Zurich | University of Oxford | University of Trento | PKU | IIAIVerified email at vision.ee.ethz.ch
Hongwei YongResearch Assistant Professor in the Hong Kong Polytechnic UniversityVerified email at polyu.edu.hk
Yulun ZhangETH ZurichVerified email at ethz.ch
Wen LiData Intelligence Group, UESTCVerified email at uestc.edu.cn
Jiaxi JiangPhD student, ETH ZurichVerified email at inf.ethz.ch
Wenguan WangZhejiang UniversityVerified email at zju.edu.cn

Kai Zhang

Other names张凯

Postdoctoral Researcher, ETH Zurich

Verified email at vision.ee.ethz.ch - Homepage

Image Restoration Inverse Problems Computational Imaging


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Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising K Zhang, W Zuo, Y Chen, D Meng, L Zhang IEEE TIP 2017, code: https://github.com/cszn/KAIR, 2017	5900	2017
Learning Deep CNN Denoiser Prior for Image Restoration K Zhang, W Zuo, S Gu, L Zhang CVPR 2017, code: https://github.com/cszn/DPIR, 2017	1659	2017
FFDNet: Toward a fast and flexible solution for CNN based image denoising K Zhang, W Zuo, L Zhang IEEE TIP 2018, code: https://github.com/cszn/KAIR, 2018	1617	2018
Ntire 2017 challenge on single image super-resolution: Methods and results R Timofte, E Agustsson, L Van Gool, MH Yang, L Zhang, B Lim, S Son, ... CVPRW 2017, 2017	1246	2017
Learning a single convolutional super-resolution network for multiple degradations K Zhang, W Zuo, L Zhang CVPR 2018, code: https://github.com/cszn/KAIR, 2018	810	2018
Toward convolutional blind denoising of real photographs S Guo, Z Yan, K Zhang, W Zuo, L Zhang CVPR 2019, 2019	723	2019
SwinIR: Image Restoration using Swin Transformer J Liang, J Cao, G Sun, K Zhang*, L Van Gool, R Timofte ICCV Workshops; code: https://github.com/JingyunLiang/SwinIR, 2021	659	2021
Multi-level wavelet-CNN for image restoration P Liu, H Zhang, K Zhang, L Lin, W Zuo CVPRW 2018, 2018	528	2018
End-to-End Blind Image Quality Assessment Using Deep Neural Networks K Ma, W Liu, K Zhang, Z Duanmu, Z Wang, W Zuo IEEE TIP 2018, 2018	384	2018
Deep Unfolding Network for Image Super-Resolution K Zhang, L Van Gool, R Timofte CVPR 2020, code: https://github.com/cszn/USRNet, 2020	345	2020
Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels K Zhang, W Zuo, L Zhang CVPR 2019, code: https://github.com/cszn/DPSR, 2019	304	2019
Plug-and-Play Image Restoration with Deep Denoiser Prior K Zhang, Y Li, W Zuo, L Zhang, L Van Gool, R Timofte IEEE TPAMI, code: https://github.com/cszn/DPIR, 2021	289	2021
Ntire 2018 challenge on single image super-resolution: Methods and results R Timofte, S Gu, J Wu, L Van Gool CVPRW 2018, 2018	283	2018
LocalViT: Bringing Locality to Vision Transformers Y Li, K Zhang, J Cao, R Timofte, L Van Gool arXiv preprint arXiv:2104.05707, 2021	250	2021
Extreme learning machine and adaptive sparse representation for image classification J Cao, K Zhang, M Luo, C Yin, X Lai Neural networks 81, 91-102, 2016	210	2016
Outlier-robust extreme learning machine for regression problems K Zhang, M Luo Neurocomputing 151, 1519-1527, 2015	180	2015
Neural Blind Deconvolution Using Deep Priors D Ren, K Zhang, Q Wang, Q Hu, W Zuo CVPR 2020, code: https://github.com/csdwren/SelfDeblur, 2020	179	2020
Designing a Practical Degradation Model for Deep Blind Image Super-Resolution K Zhang, J Liang, L Van Gool, R Timofte ICCV 2021; https://github.com/cszn/BSRGAN, 2021	178	2021
Ntire 2019 challenge on real image super-resolution: Methods and results J Cai, S Gu, R Timofte, L Zhang CVPRW 2019, 2019	101	2019
A hybrid approach combining extreme learning machine and sparse representation for image classification M Luo, K Zhang Engineering Applications of Artificial Intelligence 27, 228-235, 2014	97	2014

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