I am currently a postdoctoral researcher at Computer Vision Lab, ETH Zurich, Switzerland, working with
Prof. Luc Van Gool
and Dr. Radu Timofte.
Before that, I received my Ph.D. degree from School of Computer Science and Technology, Harbin Institute of Technology, China, in 2019,
under the supervision of Prof. Lei Zhang
and Prof. Wangmeng Zuo.
I was a research assistant from July, 2015 to July, 2017 and from July, 2018 to April, 2019 in Department of Computing of The Hong Kong Polytechnic University.
I work in the field of image processing, specializing in particular on developing deep learning techniques for inverse problems in low-level computer vision.
I mainly investigate how to incorporate traditional model-based method and deep learning-based method for flexible, effective, efficient and interpretable image restoration.
Recently, I focus on the following research topics:
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Plug-and-Play Image Restoration with Deep Denoiser Prior
Kai Zhang, Yawei Li, Wangmeng Zuo, Lei Zhang, Luc Van Gool and Radu Timofte
ArXiv, 2020.
[Paper]
[PyTorch Code]
[BibTex]
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AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
Kai Zhang, Martin Danelljan, Yawei Li, Radu Timofte and others
European Conference on Computer Vision Workshops(ECCVW), 2020.
[Paper]
[BibTex]
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Deep Unfolding Network for Image Super-Resolution
Kai Zhang, Luc Van Gool, Radu Timofte
IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), 2020.
[Paper]
[PyTorch Code]
[BibTex]
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Neural Blind Deconvolution Using Deep Priors
Dongwei Ren, Kai Zhang, Qilong Wang, Qinghua Hu, Wangmeng Zuo
IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), 2020.
[Paper]
[PyTorch Code]
[BibTex]
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NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte, and others
IEEE International Conference on Computer Vision and Pattern Recognition Workshops(CVPRW), 2020.
[Paper]
[BibTex]
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AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte, and others
IEEE International Conference on Computer Vision Workshops (ICCVW), 2019.
[Paper]
[PyTorch Code of Winner]
[BibTex]
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Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels
Kai Zhang, Wangmeng Zuo, Lei Zhang
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[Paper]
[PyTorch Code]
[BibTex]
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Learning a Single Convolutional Super-Resolution Network for Multiple Degradations
Kai Zhang, Wangmeng Zuo, Lei Zhang
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[Paper]
[Matlab Code]
[PyTorch Code]
[BibTex]
[Citations: 150+] |
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Learning Deep CNN Denoiser Prior for Image Restoration
Kai Zhang, Wangmeng Zuo, Shuhang Gu, Lei Zhang
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
[Paper]
[Matlab Code]
[BibTex]
[Citations: 500+] |
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FFDNet: Toward a Fast and Flexible Solution for CNN-based Image Denoising
Kai Zhang, Wangmeng Zuo, Lei Zhang
IEEE Transactions on Image Processing (TIP), 27(9): 4608-4622, 2018.
[Paper]
[Matlab Code]
[PyTorch Code]
[BibTex]
[Citations: 300+] |
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Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, Lei Zhang
IEEE Transactions on Image Processing (TIP), 26(7): 3142-3155, 2017.
[Paper]
[Matlab Code]
[PyTorch Code]
[BibTex]
[Citations: 1700+] |
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End-to-End Blind Image Quality Assessment Using Deep Neural Networks
Kede Ma, Wentao Liu, Kai Zhang, Zhengfang Duanmu, Zhou Wang, Wangmeng Zuo
IEEE Transactions on Image Processing (TIP), 27(3): 1202-1213, 2017.
[Paper]
[Project Page]
[BibTex]
[Citations: 90+] |
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Toward Convolutional Blind Denoising of Real Photographs
Shi Guo, Zifei Yan, Kai Zhang, Wangmeng Zuo, Lei Zhang
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[Paper]
[Code]
[BibTex]
[Citations: 80+] |
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Convolutional Neural Networks for Image Denoising and Restoration (Book chapter)
Wangmeng Zuo, Kai Zhang, Lei Zhang
In: M. Bertalmio (eds.), Denoising of Photographic Images and Video: Fundamentals, Open Challenges and New Trends, Springer, 2018.
[Paper]
[BibTex] |
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Joint Learning of Multiple Regressors for Single Image Super-Resolution
Kai Zhang, Baoquan Wang, Wangmeng Zuo, Hongzhi Zhang, Lei Zhang.
IEEE Signal Processing Letters (SPL), 23, (1): 102-106, 2016.
[Paper]
[BibTex]
[Citations: 30+]
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Revisiting Single Image Super-Resolution Under Internet Environment: Blur Kernels and Reconstruction Algorithms
Kai Zhang, Xiaoyu Zhou, Hongzhi Zhang, Wangmeng Zuo.
Pacific Rim Conference on Multimedia (PCM), 2015: 677-687
[Paper]
[BibTex]
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Services
Workshop Organizers:
Co-organizer of ECCV 2020 Workshop on Advanced Image Manipulation (AIM).
Co-organizer of CVPR 2020 Workshop on New Trends in Image Restoration and Enhancement (NTIRE).
Co-organizer of ICCV 2019 Workshop on Advanced Image Manipulation (AIM).
Journal Reviewer:
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- International Journal of Computer Vision (IJCV)
- IEEE Transactions on Image Processing (TIP)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
- Computer Vision and Image Understanding (CVIU)
- Signal Processing Letters (SPL)
Conference Reviewer:
- IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- International Conference on Computer Vision (ICCV)
- European Conference on Computer Vision (ECCV)
- AAAI Conference on Artificial Intelligence (AAAI)
- International Joint Conferences on Artificial Intelligence (IJCAI)
Awards
- First Prize of Natural Science Award of Heilongjiang Province, 2020
- Outstanding student paper award of HIT, 2018
- Fourth place of NTIRE 2018 challenge on single image super-resolution, 2018
- National scholarship for doctoral students, 2017
- Outstanding student paper award of HIT, 2017
- First prize of GUANGXI International Academic Forum, 2017
- Best poster award of Valse2017, 2017
Collaborators
