Kai Zhang

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Wangmeng ZuoSchool of Computer Science and Technology, Harbin Institute of TechnologyVerified email at hit.edu.cn
Lei ZhangChair Professor, Dept. of Computing, The Hong Kong Polytechnic UniversityVerified email at comp.polyu.edu.hk
Radu TimofteUniversity of Würzburg & ETH ZurichVerified email at vision.ee.ethz.ch
Luc Van Goolprofessor computer vision ETH Zurich & KU Leuven, Head Toyota Lab TRACE @ KUL & ETHVerified email at ethz.ch
Shuhang GuETH, ZurichVerified email at vision.ee.ethz.ch
Yunjin CHENAlibaba CloudVerified email at alibaba-inc.com
Yawei LiETH ZurichVerified email at vision.ee.ethz.ch
Shi GuoPhD student in HK PolyUVerified email at comp.polyu.edu.hk
Pengju LiuHarbin Institute of TechnologyVerified email at stu.hit.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
Jingyun LiangPhD student, Computer Vision Lab, ETH ZurichVerified email at vision.ee.ethz.ch
Jiezhang CaoPhD Student, ETH ZürichVerified email at ee.ethz.ch
Dongwei RenHarbin Institute of TechnologyVerified email at hit.edu.cn
Qilong WangTianjin UniversityVerified email at tju.edu.cn
Qinghua HuProfessor of Computer Science, Tianjin UniversityVerified email at tju.edu.cn
Hongwei YongPhD candidate in the Hong Kong Polytechnic UniversityVerified email at comp.polyu.edu.hk
Martin DanelljanResearcher, ETH ZurichVerified email at vision.ee.ethz.ch
Guolei SunETH ZurichVerified email at vision.ee.ethz.ch
Wen LiData Intelligence Group, UESTCVerified email at uestc.edu.cn

Kai Zhang

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	3555	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	1043	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	835	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	788	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	452	2018
Toward convolutional blind denoising of real photographs S Guo, Z Yan, K Zhang, W Zuo, L Zhang CVPR 2019, 2019	316	2019
Multi-level wavelet-CNN for image restoration P Liu, H Zhang, K Zhang, L Lin, W Zuo CVPRW 2018, 2018	260	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	216	2018
Ntire 2018 challenge on single image super-resolution: Methods and results R Timofte, S Gu, J Wu, L Van Gool CVPRW 2018, 2018	194	2018
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	167	2016
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	153	2019
Outlier-robust extreme learning machine for regression problems K Zhang, M Luo Neurocomputing 151, 1519-1527, 2015	143	2015
Deep Unfolding Network for Image Super-Resolution K Zhang, L Van Gool, R Timofte CVPR 2020, code: https://github.com/cszn/USRNet, 2020	101	2020
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	88	2014
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	67	2020
Ntire 2019 challenge on real image super-resolution: Methods and results J Cai, S Gu, R Timofte, L Zhang CVPRW 2019, 2019	64	2019
Color image demosaicking via deep residual learning R Tan, K Zhang, W Zuo, L Zhang 2017 IEEE International Conference on Multimedia and Expo (ICME), 793-798, 2017	55	2017
Ntire 2019 challenge on real image denoising: Methods and results A Abdelhamed, R Timofte, MS Brown CVPRW 2019, 2019	53	2019
Joint Learning of Multiple Regressors for Single Image Super-Resolution K Zhang, B Wang, W Zuo, H Zhang, L Zhang IEEE Signal Processing Letters 23 (1), 102-106, 2016	42	2016
Extreme Learning Machine With Affine Transformation Inputs in an Activation Function J Cao, K Zhang, H Yong, X Lai, B Chen, Z Lin IEEE TNNLS 2018, 2018	35	2018

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