Fred Tung

Bio

I am a PhD candidate with the University of British Columbia's Laboratory for Computational Intelligence. My supervisor is Jim Little. I received the MASc degree from the University of Waterloo as a member of the Vision and Image Processing Lab. My research interests are in:
1. How to efficiently search large sources of data, especially in the context of computer vision applications;
2. Nonparametric (exemplar-based) algorithms for solving scene understanding problems, such as scene parsing of images and video.

ftung [at] cs.ubc.ca

Teaching

Jan. 2016CPSC 425 Computer Vision

Publications

SSP: Supervised sparse projections for large-scale retrieval in high dimensions
F. Tung and J.J. Little
Asian Conference on Computer Vision (ACCV), 2016
[pre-print | code]
Factorized binary codes for large-scale nearest neighbor search
F. Tung and J.J. Little
British Machine Vision Conference (BMVC), 2016
[pdf]
Exploiting random RGB and sparse features for camera pose estimation
L. Meng, J. Chen, F. Tung, J.J. Little, and C. De Silva
British Machine Vision Conference (BMVC), 2016
[pdf, data]
Scene parsing by nonparametric label transfer of content-adaptive windows
F. Tung and J.J. Little
Computer Vision and Image Understanding (CVIU), vol. 143, pp. 191-200, 2016
[pre-print | link]
Improving scene attribute recognition using web-scale object detectors
F. Tung and J.J. Little
Computer Vision and Image Understanding (CVIU), vol. 138, pp. 86-91, 2015
[pre-print | link]
Bank of quantization models: A data-specific approach to learning binary codes for large-scale retrieval applications
F. Tung, J. Martinez, H.H. Hoos, and J.J. Little
IEEE Winter Conference on Applications of Computer Vision (WACV), 2015
[pre-print | link]
CollageParsing: Nonparametric scene parsing by adaptive overlapping windows
F. Tung and J.J. Little
European Conference on Computer Vision (ECCV), 2014
[pre-print | link]
Improving scene attribute recognition using web-scale object detectors
F. Tung and J.J. Little
International Workshop on Parts and Attributes (at ECCV), 2014
Polynomial self-similarity for object classification
F. Tung and A. Wong
IEEE International Conference on Multimedia and Expo, short papers track, 2013
A decoupled approach to illumination-robust optical flow estimation
A. Kumar, F. Tung, A. Wong, and D.A. Clausi
IEEE Transactions on Image Processing, vol. 22, no. 10, pp. 4136-4147, 2013
Goal-based trajectory analysis for unusual behaviour detection in intelligent surveillance
F. Tung, J.S. Zelek, and D.A. Clausi
Image and Vision Computing, vol. 29, pp. 230-240, 2011
Enabling scalable spectral clustering for image segmentation
F. Tung, A. Wong, and D.A. Clausi
Pattern Recognition, vol. 43, pp. 4069-4076, 2010
Efficient target recovery using STAGE for mean-shift tracking
F. Tung, J.S. Zelek, and D.A. Clausi
Canadian Conference on Computer and Robot Vision, 2009