Jinjin Gu

11 object(s)
 

Research

Reseach

I study computer vision, image processing. I am also interested in the interpretability of deep learning algorithms and the applications of machine learning in industrial.

Research Collection:
[Interpretable Low-Level Vision]: Research works about interpreting and explaining low-level vision networks.

Publications

Check my Google Scholar Profile for more information
* = equal contribution, and ✉ = corresponding author

Conference Publications

Super-Resolution by Predicting Offsets: An Ultra-Efficient Super-Resolution Network for Rasterized Images.
Jinjin Gu, Haoming Cai, Chenyu Dong, Ruofan Zhang, Yulun Zhang, Wenming Yang, Chun Yuan.
European Conference on Computer Vision (ECCV), 2022

Rethinking the Pipeline of Demosaicing, Denoising and Super-Resolution.
Guocheng Qian*, Yuanhao Wang*, Chao Dong, Jimmy S. Ren, Wolfgang Heidrich, Bernard Ghanem, Jinjin Gu
International Conference on Computational Photography (ICCP), 2022
[arXiv] [Code] [Dataset]

Reflash Dropout in Image Super-Resolution.
Xiangtao Kong, Xina Liu, Jinjin Gu, Yu Qiao, Chao Dong
Computer Vision and Pattern Recognition (CVPR), 2022
[PDF] [Project and Code]
[Talk 2022.5 (CN)]

A Texture-based Error Analysis for Image Super-Resolution.
Salma Abdel Magid, Zudi Lin, Donglai Wei, Yulun Zhang, Jinjin Gu, Hanspeter Pfister
Computer Vision and Pattern Recognition (CVPR), 2022
[PDF]

Interpreting Super-Resolution Networks with Local Attribution Maps.
Jinjin Gu, Chao Dong
Computer Vision and Pattern Recognition (CVPR), 2021
[PDF] [Project] [Colab Demo] [Youtube] [Bilibili]
[Talk 2021.3 (CN)] [Talk 2021.5 (CN)] [Talk 2021.7 (CN)] [Talk 2021.9 (CN)]

PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration.
Jinjin Gu, Haoming Cai, Haoyu Chen, Xiaoxing Ye, Jimmy S. Ren, Chao Dong.
European Conference on Computer Vision (ECCV), 2020
[PDF] [Project] [Dataset] [Extended]
[Benchmark] [Youtube] [Bilibili]
[CVPR 2021 NTIRE Challenge]
[CVPR 2022 NTIRE Challenge (Full-Reference) (No-Reference)]

Image Processing Using Multi-Code GAN Prior.
Jinjin Gu, Yujun Shen, Bolei Zhou.
Computer Vision and Pattern Recognition (CVPR), 2020
[PDF] [Project] [Code]

Interpreting the Latent Space of GANs for Semantic Face Editing.
Yujun Shen, Jinjin Gu, Xiaoou Tang, Bolei Zhou.
Computer Vision and Pattern Recognition (CVPR), 2020
[PDF] [Project] [Code] [Video]

Blind Super-Resolution With Iterative Kernel Correction.
Jinjin Gu, Hannan Lu, Wangmeng Zuo, Chao Dong.
Computer Vision and Pattern Recognition (CVPR), 2019
[PDF] [Project]

Journal Publications

AI-Enabled Image Fraud in Scientific Publications.
Jinjin Gu, Xinlei Wang, Chenang Li, Junhua Zhao, Weijin Fu, Gaoqi Liang, Jing Qiu.
Patterns, Cell Press, 2022
[PDF]

Electricity-Consumption Data Reveals the Economic Impact and Industry Recovery during the Pandemic.
Xinlei Wang*, Caomingzhe Si*, Jinjin Gu, Guolong Liu, Wenxuan Liu, Jing Qiu, Junhua Zhao.
Scientific Reports, Volume 11, Article number: 19960, 2021
[PDF] [HTML]

Super Resolution Perception for Improving Data Completeness in Smart Grid State Estimation.
Gaoqi Liang, Guolong Liu, Junhua Zhao, Yanli Liu, Jinjin Gu, Guang-Zhong Sun, Zhaoyang Dong.
Engineering, Volume 6, Issue 7, Pages 789-800, July 2020
Proceedings of the Chinese Academy of Engineering
[PDF] [Dataset]

Super Resolution Perception for Smart Meter Data.
Guolong Liu, Jinjin Gu, Junhua Zhao, Fushuan Wen, Gaoqi Liang.
Information Sciences, Volume 526, Pages 263-273, July 2020
[PDF] [Dataset]

Two-phase Hair Image Synthesis by Self-Enhancing Generative Model.
Haonan Qiu, Chuan Wang, Hang Zhu, Xiangyu Zhu, Jinjin Gu, Xiaoguang Han.
Computer Graphics Forum, Volume 38 (2019), Number 7, Pages 403-412
In Proceeding Pacific Graphics (PG), 2019
[PDF] [arXiv] [Dataset]

Workshop Publications

Blueprint Separable Residual Network for Lightweight Image Super-Resolution.
Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Jinjin Gu, Yu Qiao, Chao Dong
Computer Vision and Pattern Recognition Workshop (CVPRW), 2022
[PDF] [Challenge Report]

NTIRE 2022 Challenge on Perceptual Image Quality Assessment.
Jinjin Gu, Haoming Cai, Chao Dong, Jimmy S. Ren, Radu Timofte
Computer Vision and Pattern Recognition Workshop (CVPRW), 2022
[Challenge FR Track] [Challenge NR Track]

NTIRE 2021 Challenge on Perceptual Image Quality Assessment.
Jinjin Gu, Haoming Cai, Chao Dong, Jimmy S. Ren, Shuhang Gu, Radu Timofte
Computer Vision and Pattern Recognition Workshop (CVPRW), 2021
[PDF] [Challenge]
[Talk]

Suppressing Model Overfitting for Image Super-Resolution Networks.
Ruicheng Feng, Jinjin Gu, Chao Dong, Yu Qiao.
Computer Vision and Pattern Recognition Workshop (CVPRW), 2019
Winner, in the NTIRE Real-Image SR Challenge, CVPR
[PDF] [Challenge] [Challenge Report]

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks.
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, Chen Change Loy.
European Conference on Computer Vision Workshop (ECCVW), 2018
Champion, Region 3 in the PIRM2018-SR Challenge, ECCV
[PDF] [Code] [Challenge] [Challenge Report]

Technical Reports

Rethinking Alignment in Video Super-Resolution Transformers.
Shuwei Shi*, Jinjin Gu*, Liangbin Xie, Xintao Wang, Yujiu Yang, Chao Dong.
[arXiv] [Code]

Evaluating the Generalization Ability of Super-Resolution Networks.
Yihao Liu, Hengyuan Zhao, Jinjin Gu, Yu Qiao, Chao Dong .
[arXiv]

Discovering “Semantics” in Super-Resolution Networks.
Yihao Liu*, Anran Liu*, Jinjin Gu, Zhipeng Zhang, Wenhao Wu, Yu Qiao, Chao Dong .
[arXiv] [Project]

Blind Image Super-Resolution: A Survey and Beyond.
Anran Liu, Yihao Liu, Jinjin Gu, Yu Qiao, Chao Dong.
[arXiv]

Image Quality Assessment for Perceptual Image Restoration: A New Dataset, Benchmark and Metric.
Jinjin Gu, Haoming Cai, Haoyu Chen, Xiaoxing Ye, Jimmy S. Ren, Chao Dong.
[arXiv]

Research Projects

SenseSR - Intelligent Photography Solution for Mobile Devices.
Research at Sensetime Research, 2018
Denoising and super-resolution of multiple unaligned observation pictures with unknown noise and unknown blur under the limited computing conditions and time constraints on mobile devices.
[Technology] [Product] [Media Coverage (CN)]




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