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Zongsheng Yue (岳 宗胜) |
I am currently a research fellow at School of Computer Science and Engineering, Nanyang Technological University, working with Prof. Chen Change Loy. I received my Ph.D. degree from School of Mathematics and Statistics, Xi'an Jiaotong University, China, in 2021, under the supervision of Prof. Deyu Meng. Before that, I received my Bachelor degree from the College of Mathematics and System Science, Xinjiang University, in 2015.
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MMLab@NTU, Nanyang Technological University, Singapore Research Fellow, Apr. 2022 ~ present Supervisor: Prof. Chen Change Loy |
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Computer Vision Group, The University of Hong Kong, Hong Kong Postdoctoral Researcher, Sep. 2021 ~ Mar. 2022 Supervisor: Assoc Prof. Kenneth K.Y. Wong |
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DAMO Academy, Alibaba Group, Shenzhen, China Research Intern, Mar. 2021 ~ Sep. 2021 Supervisor: Prof. Lei Zhang |
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Department of Computing, The Hong Kong Polytechnic University, Hong Kong Research Assistant, Oct. 2018 ~ Jun. 2019 Supervisor: Prof. Lei Zhang |
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Institute of Future Cities, The Chinese University of Hong Kong, Hong Kong Research Assistant, Feb. 2017 ~ Sep. 2017 Supervisor: Prof. Leung Yee |
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Arbitrary-steps Image Super-resolution via Diffusion Inversion |
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MOWA: Multiple-in-One Image Warping Model |
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Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration |
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Efficient Diffusion Model for Image Restoration by Residual Shifting |
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Blind Image Deconvolution by Generative-based Kernel Prior and Initializer via Latent Encoding |
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DifFace: Blind Face Restoration via Diffused Error Contraction |
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Exploiting Diffusion Prior for Real-World Image Super-resolution |
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Variational Image Restoration Network |
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ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting |
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Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel |
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Semi-Supervised Video Deraining with Dynamical Rain Generator |
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From Rain Generation to Rain Removal |
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Dual Adversarial Network: Toward Real-World Noise Removal and Noise Generation |
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Variational Denoising Network: Toward Blind Noise Modeling and Removal |
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Robust Multiview Subspace Learning With Nonindependently and Nonidentically Distributed Complex Noise |
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