World's Best Scientists 2026 revealed!
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Computer Science
UK
2026

D-Index & Metrics

Computer Science

D-Index
109
Citations
44546
World Ranking
247
National Ranking
10

Research.com Recognitions

  • 2026 - Research.com Computer Science in United Kingdom Leader Award
  • 2025 - Research.com Computer Science in United Kingdom Leader Award
  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award

Overview

Shaogang Gong is affiliated with Queen Mary University of London in the United Kingdom. Their research is situated primarily in the field of Computer Science, featuring a strong focus on Computer Vision and Pattern Recognition. Within this domain, they explore various subfields including Artificial Intelligence, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, and Mechanical Engineering.

The scope of their research topics covers several specific subjects, such as:

  • Multimodal Machine Learning Applications
  • Video Surveillance and Tracking Methods
  • Domain Adaptation and Few-Shot Learning
  • Human Pose and Action Recognition
  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Video Analysis and Summarization

Shaogang Gong has contributed extensively to scientific literature, with notable recent papers including:

  • "RGB-IR Person Re-identification by Cross-Modality Similarity Preservation" (2020), published in the International Journal of Computer Vision
  • "Semi-Supervised Learning under Class Distribution Mismatch" (2020), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "Peer Collaborative Learning for Online Knowledge Distillation" (2021), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "Tracklet Self-Supervised Learning for Unsupervised Person Re-Identification" (2020), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "Collaborative Optimization and Aggregation for Decentralized Domain Generalization and Adaptation" (2021), published in the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

The frequent coauthors collaborating with Shaogang Gong include Jiabo Huang, Guile Wu, Xiatian Zhu, Hailin Jin, and Shitong Sun. These collaborations indicate a network centered on computer vision and machine learning research.

Publication venues where Shaogang Gong often publishes include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Pattern Recognition
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • International Journal of Computer Vision

Shaogang Gong has contributed significantly to advancing methods and applications in video surveillance, human action recognition, and multimodal learning, reflecting the integration of diverse computer vision techniques and domain adaptation strategies. The blend of topics and publication outlets underscores a research profile deeply embedded in addressing challenges within visual data interpretation and machine intelligence.

Best Publications

  • Facial expression recognition based on Local Binary Patterns: A comprehensive study

    Caifeng Shan;Shaogang Gong;Peter W. McOwan

  • Harmonious Attention Network for Person Re-identification

    Wei Li;Xiatian Zhu;Shaogang Gong

  • Semantic Autoencoder for Zero-Shot Learning

    Elyor Kodirov;Tao Xiang;Shaogang Gong

  • Person re-identification by probabilistic relative distance comparison

    Wei-Shi Zheng;Shaogang Gong;Tao Xiang

  • Reidentification by Relative Distance Comparison

    Wei-Shi Zheng;Shaogang Gong;Tao Xiang

  • Person Re-Identification by Support Vector Ranking

    Bryan James Prosser;Wei-Shi Zheng;Shaogang Gong;Tao Xiang

  • RGB-Infrared Cross-Modality Person Re-identification

    Ancong Wu;Wei-Shi Zheng;Hong-Xing Yu;Shaogang Gong

  • Person re-identification by video ranking

    Taiqing Wang;Shaogang Gong;Xiatian Zhu;Shengjin Wang

  • Learning a Deep Embedding Model for Zero-Shot Learning

    Li Zhang;Tao Xiang;Shaogang Gong

  • Feature mining for localised crowd counting

    Ke Chen;Chen Change Loy;Shaogang Gong;Tony Xiang

  • Learning a Discriminative Null Space for Person Re-identification

    Li Zhang;Tao Xiang;Shaogang Gong

  • Robust facial expression recognition using local binary patterns

    Caifeng Shan;Shaogang Gong;P.W. McOwan

  • Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-identification

    Jingya Wang;Xiatian Zhu;Shaogang Gong;Wei Li

  • Associating Groups of People

    Wei-Shi Zheng;Shaogang Gong;Tao Xiang

  • Transductive Multi-View Zero-Shot Learning

    Yanwei Fu;Timothy M. Hospedales;Tao Xiang;Shaogang Gong

  • Cumulative Attribute Space for Age and Crowd Density Estimation

    Ke Chen;Shaogang Gong;Tao Xiang;Chen Change Loy

  • Tracking colour objects using adaptive mixture models

    Stephen J. McKenna;Yogesh Raja;Shaogang Gong

  • Recognising action as clouds of space-time interest points

    Matteo Bregonzio;Shaogang Gong;Tao Xiang

  • Person Re-identification by Attributes.

    Ryan Layne;Timothy M. Hospedales;Shaogang Gong

  • Person Re-Identification by Deep Joint Learning of Multi-Loss Classification

    Wei Li;Xiatian Zhu;Shaogang Gong

Frequent Co-Authors

Xiatian Zhu
Xiatian Zhu University of Surrey
Timothy M. Hospedales
Timothy M. Hospedales University of Edinburgh
Chen Change Loy
Chen Change Loy Nanyang Technological University
Stephen J. McKenna
Stephen J. McKenna University of Dundee
Wei-Shi Zheng
Wei-Shi Zheng Sun Yat-sen University
Yanwei Fu
Yanwei Fu Fudan University
Caifeng Shan
Caifeng Shan Nanjing University
Kui Jia
Kui Jia South China University of Technology
Jianhuang Lai
Jianhuang Lai Sun Yat-sen University
Yi-Zhe Song
Yi-Zhe Song University of Surrey

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