Beilei Cui

The Chinese University of Hong Kong .

Photo_Cui_Beilei.jpg

Room 424, Ho Sin-Hang Engineering Building

CUHK, Shatin, N.T., Hong Kong, 999077

Email: beileicui AT link.cuhk.edu.hk

I am currently a Ph.D student at Medical Mechatronics Lab of the Department of Electronic Engineering, The Chinese University of Hong Kong, supervised by Prof. Hongliang Ren. Previously, I received my B.Eng. degree in 2021 in School of Information and Communication Engineering, University of Electronic Science and Technology of China, advised by Prof. Zhizhong Fu. I also studied at Department of Electrical and Electronic Engineering in Imperial College London and received my M.Sc degree in 2022 advised by Dr. Javier Barria.

My research interests include artificial intelligent applications in medical image analysis, robotic perception and robotic navigation. I am recently working on self-supervised monocular depth estimation, 3D reconstruction, NeRF, noisy label learning.

I am always passionate about discussion or potential cooperation opportunities so feel free to contact me via email if have related inquiries! Medical Mechatronics Lab is also open for research interns, don’t hesitate to contact me if you are interested. Specifically, Student helper programme are available for CUHK undergraduate & MSc students.

news

Jan 28, 2025 One paper on monocular 3D reconstruction is accepted by ICRA 2025.
Dec 25, 2024 One paper V2-SfMLearner on monocular depth estimation is accepted by T-ASE.
Oct 15, 2024 One paper is accepted by ROBIO!
Sep 4, 2024 One paper MMAT-OCT is accepted by Nature Communication!
Jun 18, 2024 One paper Endo-4DGS on monocular scene reconstruction is accepted by MICCAI 2024.
Jun 5, 2024 One paper on NeRF application has been accepted by ICBIR 2024.
May 14, 2024 One paper on monocular depth estimation is early accepted by MICCAI 2024.
Feb 2, 2024 One paper Endo-4DGS on monocular scene reconstruction is online.
Dec 15, 2023 One paper on monocular depth estimation with adaptation learning is accepted by IPCAI 2024.
Jun 5, 2023 One paper on noisy label learning for medical video segmentation is accepted by MICCAI 2023.

selected publications

  1. Nature Communications
    MMATOCT.jpg
    Motor-free telerobotic endomicroscopy for steerable and programmable imaging in complex curved and localized areas
    Sishen Yuan*, Chao Xu*, Beilei Cui*, Tinghua Zhang, Baijia Liang, Wu Yuan†, and Hongliang Ren†
    Nature Communications, 2024
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  2. MICCAI
    EndoDAC.jpg
    EndoDAC: Efficient Adapting Foundation Model for Self-Supervised Depth Estimation from Any Endoscopic Camera
    Beilei Cui*, Mobarakol Islam*, Long Bai*, An Wang, and Hongliang Ren†
    In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024
    Early Accept, top 11%
    arXiv Code
  3. MICCAI
    Endo-4DGS.jpg
    Endo-4DGS: Endoscopic Monocular Scene Reconstruction with 4D Gaussian Splatting
    Yiming Huang*, Beilei Cui*, Long Bai*, Ziqi Guo, Mengya Xu, and Hongliang Ren†
    In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024
    arXiv Code
  4. IPCAI
    SurgicalDINO.jpg
    Surgical-DINO: Adapter Learning of Foundation Models for Depth Estimation in Endoscopic Surgery
    Beilei Cui*, Mobarakol Islam*, Long Bai, and Hongliang Ren†
    In International Journal of Computer Assisted Radiology and Surgery (IJCARS) IPCAI, 2024
    Long Oral, Best Paper Awards Shortlist
    arXiv Code
  5. MICCAI
    MS-TFAL.jpg
    Rectifying Noisy Labels with Sequential Prior: Multi-scale Temporal Feature Affinity Learning for Robust Video Segmentation
    Beilei Cui*, Minqing Zhang*, Mengya Xu*, An Wang, Wu Yuan, and Hongliang Ren†
    In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023
    arXiv HTML Code
* indicates equal contribution; † indicates corresponding author.