Machine Intelligence Laboratory

Cambridge University Department of Engineering

Je Hyeong (John) Hong Je Hyeong Hong

Background - Research - Publications - Teaching

Position: PhD Candidate

E-mail: jhh37 [at]

Office Location: BN4-80

I am a final year PhD student in the Computer Vision group under Prof. Roberto Cipolla's guidance. My research has involved developing algorithms and strategies for low-rank optimization problems in computer vision, namely bundle adjustment in 3D vision. Throughout my PhD, I have closely worked with Dr Andrew Fitzgibbon and Dr Christopher Zach. My study has been generously funded by Microsoft Research PhD Scholarship and Toshiba Research Europe Studentship.


  1. Thesis corrections approved. Now, hoping to officially graduate in May!
  2. I'm at Snap in Los Angeles until mid-June, then off to Salt Lake City for a poster presentation at CVPR.
  3. I will be starting a new research job at the Korea Institute of Science and Technology (KIST) in Seoul from the end of June (for my 3 years of mandatory alternative military service).


I obtained BA and MEng honours degrees from the University of Cambridge. You can find my CV here.

Research Interests

  • Low-rank matrix factorization problems with missing data
  • Structure-from-motion including bundle adjustment
  • Bivariate and other nonlinear optimization problems


  • pOSE: Pseudo Object Space Error for Initialization-free Bundle Adjustment
    J.H. Hong and C. Zach
    2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), to appear.
    [ Paper ] [ Supplementary ] [ Repo ] [ Poster ] [ Video ]
  • Revisiting the Variable Projection Method for Separable Nonlinear Least Squares Problems
    J.H. Hong, C. Zach and A.W. Fitzgibbon
    2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    [ Paper ] [ Supplementary ] [ Repo ] [ Poster ] [ Video ]
  • Projective Bundle Adjustment from Arbitrary Initialization using the Variable Projection Method
    J.H. Hong, C. Zach, A.W. Fitzgibbon and R. Cipolla
    2016 European Conference on Computer Vision (ECCV)
    [ Paper ] [ Supplementary ] [ Repo ] [ Poster ]
  • Secrets of Matrix Factorization: Approximations, Numerics, Manifold Optimization and Random Restarts
    J.H. Hong and A.W. Fitzgibbon
    2015 IEEE International Conference on Computer Vision (ICCV)
    [ Paper ] [ Supplementary ] [ Repo ] [ Poster ] [ Video ]


  • Snap, Los Angeles, USA (2018): I am working with Oliver Woodford and Ed Rosten on a large-scale optimization project.
  • Oculus (Facebook), Redmond, USA (2017): I worked with Alexander Fix on an eye-tracking project, developing an optimization strategy using nonlinear least squares and the implicit function theorem.
  • Toshiba, Cambridge, UK (2015, 2017): I worked with Christopher Zach on a projective bundle adjustment project and a global structure-from-motion strategy using the Variable Projection (VarPro) method.
  • Microsoft, Cambridge, UK (2014): I worked with Andrew Fitzgibbon on a project involving low-rank matrix factorization with missing data.


  • Secrets of Matrix Factorization and its Application to Projective Bundle Adjustment
    KIST IMRC lab (Korea), Dec 2016
    ETRI (Korea), Aug 2016
  • Comparing Matrix Factorization Algorithms on a Level Playing Field [ Video ]
    Microsoft Research Cambridge (CamAIML Workshop), Mar 2016


  • Supervisor (2015-2017) for 3rd-year Cambridge engineering undergraduate students teaching in groups of pairs.
  • Teaching Assistant for a 4th year module 4F13 Machine Learning (2015).
  • Research Assistant for (2013), an online tool to help students prepare for university engineering entrance interviews.