World's Best Scientists 2026 revealed!
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Rising Stars
2025

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Rising Stars

D-Index
51
Citations
35385
World Ranking
284
National Ranking
94

Computer Science

D-Index
53
Citations
39669
World Ranking
4671
National Ranking
627

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Chao Dong is affiliated with the Shenzhen Institutes of Advanced Technology in China. Their research primarily intersects the fields of computer science and engineering, with a focus on subfields such as computer vision and pattern recognition, media technology, artificial intelligence, electrical and electronic engineering, and information systems.

The scientist's work covers several main topics, notably advanced image processing techniques, advanced vision and imaging, image and signal denoising methods, image enhancement techniques, image processing techniques and applications, image and video quality assessment, and advanced image fusion techniques.

Chao Dong has contributed extensively to academic publications with a strong presence in the following venues:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Multimedia
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Among their recent papers are:

  • "Blueprint Separable Residual Network for Efficient Image Super-Resolution," 2022, published in the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • "Video super-resolution based on deep learning: a comprehensive survey," 2022, published in Artificial Intelligence Review
  • "Blind Image Super-Resolution: A Survey and Beyond," 2022, published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Understanding Deformable Alignment in Video Super-Resolution," 2021, published in Proceedings of the AAAI Conference on Artificial Intelligence
  • "Path-Restore: Learning Network Path Selection for Image Restoration," 2021, published in IEEE Transactions on Pattern Analysis and Machine Intelligence

Frequent collaborators with Chao Dong include:

  • Yu Qiao
  • Yihao Liu
  • Jingwen He
  • Jinjin Gu
  • Xintao Wang

Best Publications

  • Image Super-Resolution Using Deep Convolutional Networks

    Chao Dong;Chen Change Loy;Kaiming He;Xiaoou Tang

  • Learning a Deep Convolutional Network for Image Super-Resolution

    Chao Dong;Chen Change Loy;Kaiming He;Xiaoou Tang

  • ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

    Xintao Wang;Ke Yu;Shixiang Wu;Jinjin Gu

  • Accelerating the Super-Resolution Convolutional Neural Network

    Chao Dong;Chen Change Loy;Xiaoou Tang

  • NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

    Radu Timofte;Eirikur Agustsson;Luc Van Gool;Ming-Hsuan Yang

  • Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

    Xintao Wang;Liangbin Xie;Chao Dong;Ying Shan

  • ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

    Xintao Wang;Ke Yu;Shixiang Wu;Jinjin Gu

  • EDVR: Video Restoration With Enhanced Deformable Convolutional Networks

    Xintao Wang;Kelvin C.K. Chan;Ke Yu;Chao Dong

  • Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform

    Xintao Wang;Ke Yu;Chao Dong;Chen Change Loy

  • Activating More Pixels in Image Super-Resolution Transformer

    Unknown

  • Compression Artifacts Reduction by a Deep Convolutional Network

    Chao Dong;Yubin Deng;Chen Change Loy;Xiaoou Tang

  • Unsupervised Image Super-Resolution Using Cycle-in-Cycle Generative Adversarial Networks

    Yuan Yuan;Siyuan Liu;Jiawei Zhang;Yongbing Zhang

  • Blind Super-Resolution With Iterative Kernel Correction

    Jinjin Gu;Hannan Lu;Wangmeng Zuo;Chao Dong

  • BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

    Kelvin C.K. Chan;Xintao Wang;Ke Yu;Chao Dong

  • RankSRGAN: Generative Adversarial Networks With Ranker for Image Super-Resolution

    Wenlong Zhang;Yihao Liu;Chao Dong;Yu Qiao

  • Efficient Image Super-Resolution Using Pixel Attention

    Hengyuan Zhao;Xiangtao Kong;Jingwen He;Yu Qiao

  • Interpreting Super-Resolution Networks with Local Attribution Maps

    Jinjin Gu;Chao Dong

  • Blueprint Separable Residual Network for Efficient Image Super-Resolution

    Unknown

  • BeautyGAN: Instance-level Facial Makeup Transfer with Deep Generative Adversarial Network

    Tingting Li;Ruihe Qian;Chao Dong;Si Liu

  • Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning

    Ke Yu;Chao Dong;Liang Lin;Chen Change Loy

  • PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration

    Jinjin Gu;Haoming Cai;Haoyu Chen;Xiaoxing Ye

  • ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic

    Xiangtao Kong;Hengyuan Zhao;Yu Qiao;Chao Dong

Frequent Co-Authors

Yu Qiao
Yu Qiao Chinese Academy of Sciences
Chen Change Loy
Chen Change Loy Nanyang Technological University
Xiaoou Tang
Xiaoou Tang Chinese University of Hong Kong
Radu Timofte
Radu Timofte University of Wurzburg
Liang Lin
Liang Lin Sun Yat-sen University
Ying Shan
Ying Shan Tencent (China)
Munchurl Kim
Munchurl Kim Korea Advanced Institute of Science and Technology
A. N. Rajagopalan
A. N. Rajagopalan Indian Institute of Technology Madras
Luc Van Gool
Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)
Wangmeng Zuo
Wangmeng Zuo Harbin Institute of Technology

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