Main > JHH37
Je Hyeong (John) Hong 
Background -
Research -
Publications -
Teaching
Position: PhD Student
E-mail: jhh37 [at] cam.ac.uk
Office Location: BN4-80
Background
I am a third year PhD student in the Computer Vision group. I work in collaboration with
Dr Andrew Fitzgibbon and
Dr Christopher Zach. My study has been generously funded by
Microsoft Research Scholarship and
Toshiba Research Europe Studentship.
Research Interests
- Bundle adjustment
- Low-rank matrix factorization problems with missing data
- Robust transformed component analysis
- Bilinear optimization problems in computer vision
Publications
- Projective Bundle Adjustment from Arbitrary Initialization using the Variable Projection Method
J. H. Hong, C. Zach, A. W. Fitzgibbon and R. Cipolla (2016)
In Proceedings of the 2016 European Conference on Computer Vision (ECCV), 477--493
[ Paper ] [ Supplementary document ] [ Code ] [ Poster ]
- Secrets of Matrix Factorization: Approximations, Numerics, Manifold Optimization and Random Restarts
J. H. Hong and A. W. Fitzgibbon (2015)
In Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV), 4130--4138
[ Paper ] [ Supplementary document ] [ Code ] [ Poster ] [ Video ]
Talk
- Comparing Matrix Factorization Algorithms on a Level Playing Field
At the 2016 Cambridge Artificial Intelligence and Machine Learning in Cambridge (CamAIML) workshop, 18 March 2016
[ Video ]
Other Publication
- Bayesian Error Propagation for a Kinetic Model of n-Propylbenzene Oxidation in a Shock Tube
S. Mosbach, J. H. Hong, G. P. E. Brownbridge, M. Kraft, S. Gudiyella, and K. Brezinsky (2014)
International Journal of Chemical Kinetics, 46(7): 389--404
Internships
- July - Oct 2015: I worked at Toshiba Research Europe as a research intern for 13 weeks working on the projective bundle adjustment project.
- July - Oct 2014: I interned at Microsoft Research Cambridge for 12 weeks working on the problem of low-rank matrix factorization with missing data.
Teaching Experience
Teaching Assistant
- Part 2B 4F13 Machine Learning (2015)
Supervisions
- Part 2A 3M1 Mathematical Methods (2015, 2016)
- Part 2A 3F1 Signals and Systems (2015)
- Part 2A 3F3 Signal and Pattern Processing (2015)
Lab Demonstrations
- Part 1B Computing (MATLAB) (2014, 2015, 2016)
- Part 1B I1 Spectrum Analysis (2016)
- Part 2A SF2 Image Processing (2014, 2015, 2016)
- Part 2A 3F6 Object-oriented Programming (2015, 2016)
- Part 1B Computing (C++) (2015, 2016)
- Part 1A Microprocessors (2014)
Research Assistant
