I am currently a postdoctoral researcher at Computer Vision Lab, ETH Zurich, Switzerland, working with
Prof. Luc Van Gool
and Prof. 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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Practical Blind Denoising via Swin-Conv-UNet and Data Synthesis
Kai Zhang, Yawei Li, Jingyun Liang, Jiezhang Cao, Yulun Zhang, Tao Tang, Radu Timofte and Luc Van Gool
ArXiv, 2022.
[Paper]
[PyTorch Testing Code]
[BibTex]
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SwinIR: Image Restoration Using Swin Transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang*, Luc Van Gool and Radu Timofte
IEEE International Conference on Computer Vision Workshops (ICCVW), 2021.
[Paper]
[PyTorch Testing Code]
[PyTorch Training Code]
[BibTex]
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Designing a Practical Degradation Model for Deep Blind Image Super-Resolution
Kai Zhang, Jingyun Liang, Luc Van Gool and Radu Timofte
IEEE International Conference on Computer Vision (ICCV), 2021.
[Paper]
[PyTorch Code]
[BibTex]
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Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling
Jingyun Liang, Andreas Lugmayr, Kai Zhang*, Martin Danelljan, Luc Van Gool and Radu Timofte
IEEE International Conference on Computer Vision (ICCV), 2021.
[Paper]
[PyTorch Code]
[BibTex]
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Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution
Jingyun Liang, Guolei Sun, Kai Zhang*, Luc Van Gool and Radu Timofte
IEEE International Conference on Computer Vision (ICCV), 2021.
[Paper]
[PyTorch Code]
[BibTex]
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Towards Flexible Blind JPEG Artifacts Removal
Jiaxi Jiang, Kai Zhang* and Radu Timofte
IEEE International Conference on Computer Vision (ICCV), 2021.
[Paper]
[PyTorch Code]
[BibTex]
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Flow-based Kernel Prior with Application to Blind Super-Resolution
Jingyun Liang, Kai Zhang*, Shuhang Gu, Luc Van Gool, Radu Timofte
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[Paper]
[PyTorch Code]
[BibTex]
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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
IEEE Transactions on Pattern Analysis and Machine Intelligence(IEEE TPAMI), 2021.
[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)
Students Co-supervised
PhD students:
Master students:
- Jiaxi Jiang, 2020/09 - 2021/05, (one ICCV 2021 paper)
Awards
- Excellent Doctoral Dissertation of HIT, 2021
- 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