Ming Hu

Ph.D Candidate
MMAI Lab
Faculty of Engineering
Monash University

Email: ming.hu(at)monash.edu


Scholar profile github hompage

Biography

I am a second-year Ph.D student in Monash Medical AI Group (MMAI) at Monash University under the supervision of Dr. Peibo Duan, Prof. Juxi Leitner and Prof. Zongyuan Ge.

Areas of Interest

Medical Image/Video, Surgical Vision, Generative Model, LLMs

News

  • [09/2023] [NeurIPS 2023 D&B Track] One paper (NurViD) is selected by NeurIPS 2023 Track Datasets and Benchmarks.
  • [02/2023] [CVPR 2023] One paper (MammalNet) is selected by CVPR 2023.
  • [08/2022] I join the MMAI Lab at Monash University to pursue my doctoral degree.

Selected Publications

For complete list of publications, CLICK HERE.

    HGCLIP: Exploring Vision-Language Models with Graph Representations for Hierarchical Understanding

    Peng Xia, Xingtong Yu, Ming Hu, Lie Ju, Zhiyong Wang, Peibo Duan, Zongyuan Ge
    [arXiv] [Code]

    LMPT: Prompt Tuning with Class-Specific Embedding Loss for Long-tailed Multi-Label Visual Recognition

    Peng Xia, Di Xu, Lie Ju, Ming Hu, Zongyuan Ge
    [arXiv] [Code]

    NurViD: A Large Expert-Level Video Database for Nursing Procedure Activity Understanding

    Ming Hu*, Lin Wang*, Siyuan Yan*, Don Ma*, Qingli Ren, Peng Xia, Wei Feng, Peibo Duan, Lie Ju, Zongyuan Ge
    NeurIPS 2023 Track Datasets and Benchmarks
    [arXiv] [Code]

    MammalNet: A Large-scale Video Benchmark for Mammal Recognition and Behavior Understanding

    Jun Chen*, Ming Hu*, Darren J Coker, Michael L Berumen, Blair Costelloe, Sara Beery, Anna Rohrbach, Mohamed Elhoseiny
    CVPR 2023
    [Hompage] [Paper] [Code]

    Efficient Self-supervised Vision Pretraining with Local Masked Reconstruction

    Jun Chen, Ming Hu, Boyang Li, Mohamed Elhoseiny
    [arXiv] [Code]


    For complete list of publications, CLICK HERE.

Experiences