刘小亮（Xiaoliang Liu）

Main | Adversarial Attack | Adversarial Robustness

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Xiaoliang Liu

Email: 20249197@wzbc.edu.cn

Homepage: abeliuxl.github.io

School of Information Engineering, Wenzhou Business College  |  Robotics Intelligence and Neural Computing (RINC) Research Group, Nanjing University

Latest Updates

  • 2024-11-05: Complete and submit the paper "Region-Guided Attack on the Segment Anything Model (SAM)".
  • 2024-08-20: "RADAP: A Robust and Adaptive Defense Against Diverse Adversarial Patches on Face Recognition" accepted by *Pattern Recognition*.
  • 2024-06-20: Successfully graduated with a PhD.
  • 2024-05-23: Successfully passed the PhD dissertation defense.
  • 2024-03-31: Updated the paper link.

    • Education

    2018.09 - 2024.06 Nanjing University, Ph.D. in Computer Science and Technology, Member of RINC Group, Supervisor: Prof. Furao Shen

    2016.09 - 2018.07 Nanjing University, M.S. in Computer Science and Technology, Member of RINC Group, Supervisor: Prof. Furao Shen

    2009.09 - 2014.07 Fujian University of Technology, B.S. in Communication Engineering

    Research Interests

    Research Achievements

      Published Papers:

    1. Xiaoliang Liu, Furao Shen, Jian Zhao, Changhai Nie. RADAP: A Robust and Adaptive Defense Against Diverse Adversarial Patches on Face Recognition[J]. Pattern Recognition (2024): 110915. [Paper] (CCF-B，SCI，JCR-Q1)
    2. Xiaoliang Liu, Furao Shen, Jian Zhao and Changhai Nie. EAP: An effective black-box impersonation adversarial patch attack method on face recognition in the physical world[J]. Neurocomputing, 2024: 127517. [Paper] (CCF-C，SCI，JCR-Q2)
    3. Xiaoliang Liu, Furao Shen, Jian Zhao and Changhai Nie. Self-supervised learning of monocular 3D geometry understanding with two-and three-view geometric constraints[J]. The Visual Computer, 2024, 40(2): 1193-1204. [Paper] (CCF-C，SCI，JCR-Q2)
    4. Xiaoliang Liu, Furao Shen, Jian Zhao and Changhai Nie. RandoMix: a mixed sample data augmentation method with multiple mixed modes[J]. Multimedia Tools and Applications, 2024: 1-17. [Paper] (CCF-C，SCI，JCR-Q2)
    5. Xiaoliang Liu, Furao Shen, Jian Zhao and Changhai Nie. AugRmixAT: A data processing and training method for improving multiple robustness and generalization performance [C]. IEEE International Conference on Multimedia and Expo (ICME). 2022: 1-6. [Paper] (CCF-B，EI)

      6. Submitted Papers:

    6. Xiaoliang Liu, Furao Shen, Feng Han, Jian Zhao and Changhai Nie. NeRFTAP: Enhancing transferability of adversarial patches on face recognition using neural radiance fields[J]. arXiv preprint arXiv:2311.17332, 2023. [Paper] (SCI，Under Review)
    7. Xiaoliang Liu, Furao Shen and Jian Zhao. Region-Guided Attack on the Segment Anything Model (SAM)[J]. arXiv preprint arXiv:2411.02974, 2024. [Paper] (SCI，Submitted to Journal)

      8. Patents:

    8. Furao Shen, Kepan Gao, Xiaoliang Liu, et al. A method for indoor localization by fusing UWB and LiDAR: 202011520518[P] [2024-02-28].

      9. Book Chapters:

    9. Furao Shen. Self-Organizing Incremental Learning Neural Networks[M]. Electronic Industry Press, September 2023. (Chapter 1: Mathematical Foundations)

    Awards

  • 2022.08 - 2023.03, the First Greater Bay Area (Huangpu) International Algorithm Competition, Adversarial Robustness Defense Algorithm for Deep Learning Models, Finalist Prize. (Individual Participation)

    • Research Projects

  • State Grid Corporation of China Headquarters Science and Technology Project, Research and Application of Substation HD Video and Robot Joint Inspection Technology Based on Multi-Dimensional Image Intelligent Matching and Recognition, Project Number: 520950200009. (Participant)
  • Ministry of Science and Technology Major Project - the STI 2030-Major Projects of China, Efficient Learning Mechanism of Spiking Networks Based on Neural Plasticity and Brain-Inspired Intelligence System, Grant Nos: 2021ZD0201300. (Participant)
  • National Natural Science Foundation of China General Program, Research on Novel Neural Networks for Incremental Unsupervised Learning, Grant Nos: 62276127. (Participant)

    • Research Services

  • IEEE Transactions on Circuits and Systems for Video Technology (TCSVT, Peer Reviewer)

    • Other Information