Gang Wang

Gang Wang

Assoc. Prof. in BIBMS/CIBR/UESTC

Gang WANG (王剛)

Following the pioneer D. Marr’s theory, I mainly focus on computational vision inspired by neuroscience, seeking favorable solutions for motion/static feature extraction and visual object detection/tracking. My current positions include:

    📩 Please feel free to contact me: g_wang@foxmail.com / gang.wang@uestc.edu.cn

🔥 News & Events

  • 📣 NAIVE实验室正在招募工程师，长期招收硕博生/保送生/实习生. Join Us!
  • 2025.05:  🎉 1 paper accepted by ICML2025 (CCF-A).
  • 2025.04:  🎉 1 paper accepted by IJCAI2025 (CCF-A).
  • 2025.03:  🎉 1 paper accepted by CVPR2025 (CCF-A).
  • 2025.01:  🎉 1 paper accepted in Frontiers in Computational Neuroscience (IF=2.1, Q2).
  • 2024.11:  🎉 1 paper accepted in PLOS Biology (IF=7.8, Q1).
  • 2024.09:   helped organize the symposium Brain Inspired Computing at the CNS2024 (organized by Prof. Luping Shi).
  • 2024.09:  🎉 newly listed in the 2024 Beijing Nova Program (interdiscipline).
  • 2024.08:  🎉 1 paper accepted in IEEE Trans. on Intelligent Transportation Systems (IF=7.9, Q1).
  • 2024.08:  🎊 1 paper accepted in Frontiers in Neuroscience (IF=3.2, Q2).
  • 2024.07:  🎉 1 paper published in Applied Soft Computing (IF=7.2, Q1).
  • 2024.07:   gave a talk in CCDM2024 titled ‘Visual Motion Computing: Bio-models vs CV models’ (organized by Prof. Jian ZHAO).
  • 2024.07:   gave a talk in ISNN2024 titled ‘Bio-inspired Visual Motion Saliency Estimation for Small Video Objects with Applications’ (organized by Prof. Xiaolin HU).

🎓 Education Background

  • PhD-1: Bioscience Engineering (Mathematical Modelling), from KERMIT, Ghent University, Belgium, 2019
  • PhD-2: Measurement Techniques & Measuring Instruments, from A. Engineer. University, China, 2019
  • MSc: Control Science and Engineering, from A. Engineer. University, China, 2013
  • BSc: Telecommunications Engineering, from Dalian Maritime University, China, 2011.

🌏 Academic Services

🏆 Selected Honors & Awards

  • 2021, Young Talent on Science and Technology（高层次青年人才计划）, from the Chinese Government
  • 2022, Beijing Nova Program-innovation（北京市科技新星-创新新星）, from the Beijing Municipal Sci&Tech Commission
  • 2024, Beijing Nova Program-interdiscipline（北京市科技新星-交叉）, from the Beijing Municipal Sci&Tech Commission
  • 2021, Beijing CIBR Young Scholar (北脑青年学者), from the Beijing Municipal Sci&Tech Commission
  • 🏅2023, 1st Prize of the CVPR Anti-UAV Challenge, from the CVPR2023 Anti-UAV Challenge
  • 🏅2016, 1st Prize of the IDS Image Denoising Competition, from the IDS2016
  • 2017, Best Student Paper Nomination, from the EUSFLAT2017
  • 2019, Best Student Thesis Nomination, from the BNAIC2019
  • 2022, Outstanding AE, from the JEIT journal.

📝 Selected Publications

  1. Gang Wang#†, Xin Yang#, Liang Li, Kai Gao, Jin Gao, Jiayi Zhang, Dajun Xing, Yizheng Wang. Tiny drone object detection in videos guided by the bio-inspired magnocellular computation model[J]. Applied Soft Computing, 2024: 111892.
  2. Gang Wang#†, Carlos Lopez-Molina, Bernard De Baets. High-ISO long-exposure image denoising based on quantitative blob characterization[J]. IEEE Transactions on Image Processing, 2020, 29: 5993-6005.
  3. Bo Huang, Jianan Li, Junjie Chen, Gang Wang†, Jian Zhao†, Tingfa Xu†. Anti-UAV410: A thermal infrared benchmark and customized scheme for tracking drones in the wild[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024, 46(5): 2852-2865.
  4. Zizheng Xun, Shangzhe Di, Yulu Gao, Zongheng Tang, Gang Wang†, Si Liu, Bo Li. Linker: Learning long short-term associations for robust visual tracking [J]. IEEE Transactions on Multimedia. 2024(26): 6228-6237.
  5. Fengguang Peng, Zihan Ding, Ziming Chen, Gang Wang†, Tianrui Hui, Si Liu, Hang Shi. Region-adaptive and context-complementary cross modulation for RGB-T semantic segmentation[J]. Pattern Recognition, 2023: 110092.

      # : First author
      † : Corresponding author

🏦 Funds

  • National Natural Science Fundation of China (NSFC)
  • Beijing Natural Science Foundation
  • Beijing Nova Program Fund
  • Beijing CIBR Young Scholar Fund
  • China Scholarship Council (CSC) Scholarship
  • EUSFLAT Student Travel Grants

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🤝 Mentorship & Partnership

  • Yi-zheng Wang, Professor, CAS Member(中科院院士), BIBMS/Fudan University
  • Bernard De Baets, Professor, former President of EUSFLAT, Ghent University
  • Carlos Lopez-Molina, Professor, Universidad Publica de Navarrra
  • Institute of Automation，Chinese Academy of Sciences
  • Institute of Psychology，Chinese Academy of Sciences
  • EVOL Lab, Tele AI
  • Peking University
  • Tsinghua University
  • Beijing Normal University
  • Fudan University
  • China Electronics Technology Group Corporation
  • BIT
  • Xidian University
  • Jiangnan University
  • LG Lab
  • Beihang University
  • Beijing University of Technology

👍 Tributes

My research career has been influenced by quite a few theories and techniques proposd by the pioneers. I would like to pay tribute to these top scientists.

  • David Courtenay Marr (MIT, US)
    • He reshaped the vision computational theory, the book of whom Vision: A Computational Investigation into the Human Representation and Processing of Visual Information has always fascinated me.
  • Tony Lindeberg (KTH Royal Institute of Technology, Sweden)
    • His research subjects concern scale-space theory, early vision and image representations in terms of receptive fields. He has top telents in mathematics, and his papers usually present a lot of complex expressions. However, I love them all, because they are so elegant.
  • John F. Canny (MIT, US)
    • The famous Canny edge detetor seems easy, but the internal computation is super charming. This work tells me how the signal processing, image processing and bio-vision meet together, from a super elegant perspective.
  • Geoffrey Everest Hinton (University of Toronto, Canada)
    • He is the winner of Nobel and Turing Award, noted for his work on DCNNs that have refreshed the vision field. I bought ideas from the deep learning features that are interestingly similar to the biological V1 RFs.