profile photo

Lin Liu

Currently, I am a graduate student in the School of Information of Science and Technology, University of Science and Technology of China(USTC). Previously, I spent 8 months at the Noah's Ark Lab, Huawei Tech as a research intern, working with Prof. Jianzhuang Liu. I work closely with Shanxin Yuan, Xu Jia, Lingxi Xie and Prof. Qi Tian.

Github  /  Google Scholar  /  Zhi Hu (知乎)


  • Sep. 2019 - Now Graduate student (Master), Department of Electronic Engineering and Information Science, USTC (中国科学技术大学), supervised by Qi Tian and Wengang Zhou.
  • Sep. 2015 - Jun. 2019 Undergraduate student, Department of Information Security from USTC (中国科学技术大学), supervised by Qiang Ling.
  • News

  • Oct.2020 - I obtain the National Scholarship of China for guaduate students.
  • Sep.2020 - One paper has been accepted by NeurIPS 2020 !
  • Sep. 2020 - I join EI Innovation Lab, Cloud BU, Huawei as a student research intern.
  • Jul. 2020 - One paper has been accepted by ECCV 2020.
  • Feb. 2020 - One paper has been accepted by CVPR 2020.
  • Dec. 2019 - Our image demoieing algorithm obtains a patent.
  • Jun. 2019 - I obtain the excellent graduation thesis price of the USTC !
  • Jan. 2019 - I join Huawei Noah's Ark Lab as a research intern.
  • Projects

  • 08/2021, Low light video enhancement using 3D curve estimation at ByteDance Summer Camp 2021 .
  • Talks

  • 06/2021, "Challenges and Solutions for Intelligent Image Restoration" at NTIRE 2021 .
  • Abstract: In recent years, with the development of deep learning, image restoration and enhancement, such as image denoising and image super-resolution, have attracted more and more attention. This talk will focus on the challenges faced by image restoration and propose some solutions: 1) For the problem that real data is difficult to obtain, we introduce methods of synthesizing more real data, self-supervised learning, and fine-tuning using pre-trained models. 2) For the existing models have limited in mining useful information, we first introduce the concept of ‘guidance restoration’, then introduce some self-guidance and external-guidance methods. 3) At last, we introduce some video or burst methods for image restoration.


    I'm interested in low-level vision of computer vision and computational photography.

    Conference Papers:

  • Self-Adaptively Learning to Demoiré from Focused and Defocused Image Pairs

    Thirty-fourth Conference on Neural Information Processing Systems(NeurIPS), 2020
    Lin Liu, Shanxin Yuan, Jianzhuang Liu, Liping Bao, Gregory Slabaugh, Qi Tian

    We propose a self-adaptive learning method for image demoiréing, which uses an additional input (defocused moiré-free image) to help remove moiré patterns from the focused moiré image.

    PDF /  Codes  /  Project page

  • Wavelet-Based Dual-Branch Networkfor Image Demoireing

    European Conference on Computer Vision(ECCV), 2020
    Lin Liu, Jianzhuang Liu, Shanxin Yuan, Gregory Slabaugh, Ales Leonardis, Wengang Zhou, Qi Tian

    We propose a novel wavelet-based and dual-branch neural network for image demoireing. Our network removes moire patterns in the wavelet domain to separate the frequencies of moire patterns from the image content.

    PDF /  Codes

  • Joint Demosaicing and Denoising with Self Guidance

    Conference on Computer Vision and Pattern Recognition(CVPR), 2020
    Lin Liu, Xu Jia, Jianzhuang Liu, Qi Tian

    We propose a novel self-guidance network (SGNet) with density-map guidance and green-channel guidance for joint demosaicing and denoising (JDD). And it works well in super-resolution too.

    PDF /  Codes
  • Services

  • Reviewers of ICCV2021TOMM2021

  • Awards

    2019.09   National Network Security Scholarship (国家网络安全奖学金) (link)

    2018.09   National Scholarship (国家奖学金)  (highest national wide scholarship for students in China)

    2019.09   Outstanding Graduate Student of Anhui Province (安徽省优秀毕业生)

    2017.09   Scholarship of Institute of electronics, Chinese Academy of Sciences (中国科学院电子所奖学金)

    2017.10   中国科学技术大学机器人竞赛,第二名