Publications

2010 A. Simpson, V.Y. Tan, J. Winn, M. Svensen, C.M. Bishop, D.E. Heckerman, I. Buchan, and A. Custovic
Beyond Atopy: Multiple Patterns of Sensitization in Relation to Asthma in a Birth Cohort Study [pubmed]
in Am J Respir Crit Care Med, February 2010
Nicolas Le Roux, Nicolas Heess, Jamie Shotton, and John Winn
Learning a generative model of images by factoring appearance and shape [pdf]
Tech report no. MSR-TR-2010-7, January 2010
Pei Yin, Antonio Criminisi, John Winn, and Irfan Essa
Bilayer Segmentation of Webcam Videos Using Tree-based Classifiers [pdf]
Trans. Pattern Analysis and Machine Intelligence (PAMI), IEEE, 2010
   
2009 I. Buchan, J. Winn, C. Bishop
A Unified Modeling Approach to Data-Intensive Healthcare [pdf]
in The Fourth Paradigm: Data-Intensive Scientific Discovery,
Edited by Tony Hey, Stewart Tansley, and Kristin Tolle
Mark Everingham, Luc Van Gool, Christopher K. I. Williams, John Winn, and Andrew Zisserman
The Pascal Visual Object Classes (VOC) Challenge [pdf]
International Journal of Computer Vision (IJCV), Springer Verlag, September 2009
J. Shotton, J. Winn, C. Rother and A. Criminisi
TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Appearance, Shape and Context. [pdf]
International Journal on Computer Vision (IJCV), special issue, Vol 81, Issue 1,pp 2 , 2009
  K. Ni, A. Kannan, A. Criminisi and J. Winn
Epitomic Location Recognition. [pdf]
IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI special issue), IEEE, 2009
  M. Rattray, O. Stegle, K. Sharp, and J. Winn
Inference algorithms and learning theory for Bayesian sparse factor analysis [pdf]
International Workshop on Statistical-Mechanical Informatics 2009, Journal of Physics: Conference Series, 2009
   
2008 T. Minka and J. Winn
Gates  [pdf]
Advances in Neural Information Processing Systems, Volume 21, 2008.
Gates: A graphical notation for mixture models  [pdf] (extended form of above)
Technical report, MSR-TR-2008-185
  V. Y. F. Tan, J. Winn, A. Simpson, and A. Custovic
Immune System Modeling with Infer.NET [pdf]
IEEE International Conference on e-Science (e-Science 2008),Indianapolis, Indiana, December 2008
  K. Ni, A. Kannan, A. Criminisi and J. Winn
Epitomic location recognition  [pdf]
Proc. IEEE Computer Vision and Pattern Recognition (CVPR) 2008, Anchorage (Oral presentation)
Winner of Best Student Paper Runner Up Award
O. Stegle, A. Kannan, R. Durbin and J. Winn
Accounting for non-genetic factors improves the power of eQTL studies  [pdf]
Proc. Twelfth Annual Inter. Conf. on Research in Computational Molecular Biology (RECOMB), 2008.
 
2007 J. Huang, A. Kannan, J. Winn
Bayesian association of haplotypes and non-genetic factors to regulatory and phenotypic variation in human populations  [pdf]
Proc. of Intelligent Systems for Molecular Biology (ISMB) 2007, Vienna
S. Izadi, A. Agarwal, A. Criminisi, J. Winn, A. Blake, A. Fitzgibbon.
C-Slate: Exploring Remote Collaboration on Horizontal Multi-touch Surfaces [pdf] [project page]
Proc. IEEE Tabletop, 2007, Newport, RI, USA.
J. F. Lalonde, D. Hoiem, A. Efros, J. Winn, C. Rother and A. Criminisi.
Photo Clip Art [Project page with paper and video]
ACM Transactions on Graphics (SIGGRAPH 2007), Vol 26. No. 3, 2007 San Diego, US.
D. Hoiem, Carsten Rother, J. Winn
3D LayoutCRF for Multi-View Object Class Recognition and Segmentation [pdf]
Proc. IEEE Computer Vision and Pattern Recognition (CVPR) 2007 Minneapolis, US.
J. Lasserre, A. Kannan, J. Winn
Hybrid Learning of Large Jigsaws [pdf]
Proc. IEEE Computer Vision and Pattern Recognition (CVPR) 2007 Minneapolis, US.
P. Yin, A. Criminisi, J. Winn, I. Essa
Tree-based Classifiers for Bilayer Video Segmentation [pdf]
Proc. IEEE Computer Vision and Pattern Recognition (CVPR) 2007 Minneapolis, US.
T. Deselaers, A. Criminisi, J. Winn, A. Agarwal
Incorporating On-demand Stereo for Real Time Recognition [pdf]
Proc. IEEE Computer Vision and Pattern Recognition (CVPR) 2007 Minneapolis, US.
View a video of this system in action.
 
2006 A. Kannan, J. Winn and C. Rother
Clustering appearance and shape by learning jigsaws [pdf]
In Advances in Neural Information Processing Systems, Volume 19, 2006. (Oral presentation)
J. Winn and J. Shotton
The Layout Consistent Random Field for Recognizing and Segmenting Partially Occluded Objects [pdf]
Proc. IEEE Computer Vision and Pattern Recognition (CVPR), New York, 2006. (Oral presentation)
S. Savarese, J. Winn and A. Criminisi
Discriminative Object Class Models of Appearance and Shape by Correlatons [pdf]
Proc. IEEE Computer Vision and Pattern Recognition (CVPR), New York, 2006.
N. Jojic, J. Winn and L. Zitnick
Escaping Local Minima through Hierarchical Model Selection: Automatic Object Discovery, Segmentation, and Tracking in Video [pdf]
Proc. IEEE Computer Vision and Pattern Recognition (CVPR), New York, 2006.
J. Winn and A. Criminisi
Object Class Recognition at a Glance [pdf]
Video track: [download video (wmv - 23MB)]
Proc. IEEE Computer Vision and Pattern Recognition (CVPR), New York, 2006.
J. Shotton, J. Winn, C. Rother and  A. Criminisi
TextonBoost: Joint Appearance, Shape and Context Modeling for Mulit-Class Object Recognition and Segmentation [pdf]
European Conference on Computer Vision (ECCV) , Graz, Austria, 2006. (Oral presentation)
A. Kapoor and J. Winn
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection [pdf]
European Conference on Computer Vision (ECCV) , Graz, Austria, 2006. 
2005 J. Winn and N. Joijic.
LOCUS: Learning Object Classes with Unsupervised Segmentation [pdf]
Proc. IEEE Intl. Conf. on Computer Vision (ICCV), Beijing 2005.
View online summary of this paper.
J. Winn, A. Criminisi and T. Minka.
Object Categorization by Learned Universal Visual Dictionary [pdf]
Proc. IEEE Intl. Conf. on Computer Vision (ICCV), Beijing 2005.
J. Winn and  C. Bishop
Variational Message Passing [ps.gz] [pdf]
Journal of Machine Learning Research , Volume 6, pp. 661-694, 2005.
2004 J. Winn and  A. Blake
Generative Affine Localisation and Tracking [ps] [pdf]
Advances in Neural Information Processing Systems, Volume 17, pp. 1505-1512, 2004.
View videos from this paper.
2003 J. Winn
Variational Message Passing and its Applications [Thesis download]
Ph.D. Thesis, Department of Physics, University of Cambridge, 2003.
J. Winn and  C. Bishop
Structured Variational Distributions in VIBES [ps.gz]
In C. M. Bishop and B. Frey (Eds.), Proceedings Artificial Intelligence and Statistics , Florida, 2003.
2002 J. Winn, D. Spiegelhalter and  C. Bishop
VIBES: A Variational Inference Engine for Bayesian Networks [ps.gz]
In S. Becker, S. Thrun, and K. Obermeyer (Eds.), Advances in Neural Information Processing Systems , Volume 15, pp. 793–800, 2002.
2000 J. Winn and C. Bishop
Non-­linear Bayesian Image Modeling [ps.gz] [pdf]
In Proceedings Sixth European Conference on Computer Vision, Dublin, Volume 1, pp. 3–17. Springer, 2000.
(Recipient of the ECCV 2000 Best Paper Prize)