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

Mitigating Artifacts in Real-World Video Super-Resolution Models.
Liangbin Xie, Xintao Wang, Shuwei Shi, Jinjin Gu, Chao Dong, Ying Shan
AAAI Conference on Artificial Intelligence (AAAI), 2023
[PDF] [Code]

Rethinking Alignment in Video Super-Resolution Transformers.
Shuwei Shi*, Jinjin Gu*, Liangbin Xie, Xintao Wang, Yujiu Yang, Chao Dong.
s Neural Information Processing Systems (NeurIPS), 2022
[PDF] [Project] [Code] [Poster] [Video (CN)]

Cross Aggregation Transformer for Image Restoration.
Chen Zheng, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan.
Neural Information Processing Systems (NeurIPS), 2022
[PDF] [Code]

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
[PDF] [Code]

Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline.
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

Blind Image Super-Resolution: A Survey and Beyond.
Anran Liu, Yihao Liu, Jinjin Gu, Yu Qiao, Chao Dong.
IEEE Transactions on Pattern Analysis and Machine Intelligence TPAMI, 2022
[arXiv]

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]

Self-Supervised Intensity-Event Stereo Matching.
Jinjin Gu, Jinan Zhou, Ringo S.W Chu, Yan Chen, Jiawei Zhang, Xuanye Cheng, Song Zhang, Jimmy S. Ren.
Journal of Imaging Science and Technology JIST, 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

On the Sparsity of Image Super-resolution Network.
Chenyu Dong, Hailong Ma, Jinjin Gu, Ruofan Zhang, Jieming Li, Chun Yuan
Neural Information Processing Systems Workshop (NeurIPSW), 2022
[PDF]

Efficient Image Super-Resolution using Vast-Receptive-Field Attention.
Lin Zhou*, Haoming Cai*, Jinjin Gu, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Yu Qiao, Chao Dong
European Conference on Computer Vision Workshop (ECCVW), 2022
[PDF]

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
Winner, in the NTIRE Efficient SR Challenge, CVPR
[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

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

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

Near Real-time CO2 Emissions Based on Carbon Satellite And Artificial Intelligence.
Zhengwen Zhang, Jinjin Gu, Junhua Zhao, Jianwei Huang, Haifeng Wu
[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]

Accurate Image Restoration with Attention Retractable Transformer.
Jiale Zhang, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan.
[arXiv]

Super-Resolution Perception of Industrial Sensor Data.
Jinjin Gu, Haoyu Chen, Guolong Liu, Gaoqi Liang, Xinlei Wang, Junhua Zhao
[arXiv] [Dataset]

Single Image Reflection Removal Using Deep Encoder-Decoder Network.
Zhixiang Chi, Xiaolin Wu, Xiao Shu, Jinjin Gu
[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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