John Winn
John Winn
Principal Researcher, Machine Learning Group, Microsoft Research Cambridge
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
The pascal visual object classes (voc) challenge
M Everingham, L Van Gool, CKI Williams, J Winn, A Zisserman
International journal of computer vision 88 (2), 303-338, 2010
136312010
The pascal visual object classes challenge: A retrospective
M Everingham, SMA Eslami, L Van Gool, CKI Williams, J Winn, ...
International journal of computer vision 111 (1), 98-136, 2015
43122015
Textonboost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation
J Shotton, J Winn, C Rother, A Criminisi
European conference on computer vision, 1-15, 2006
14992006
Textonboost for image understanding: Multi-class object recognition and segmentation by jointly modeling texture, layout, and context
J Shotton, J Winn, C Rother, A Criminisi
International journal of computer vision 81 (1), 2-23, 2009
12782009
Object categorization by learned universal visual dictionary
J Winn, A Criminisi, T Minka
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 2 …, 2005
10962005
Variational message passing.
J Winn, CM Bishop, T Jaakkola
Journal of Machine Learning Research 6 (4), 2005
7012005
Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses
O Stegle, L Parts, M Piipari, J Winn, R Durbin
Nature protocols 7 (3), 500-507, 2012
5962012
Locus: Learning object classes with unsupervised segmentation
J Winn, N Jojic
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 1 …, 2005
4742005
Beyond atopy: multiple patterns of sensitization in relation to asthma in a birth cohort study
A Simpson, VYF Tan, J Winn, M Svensén, CM Bishop, DE Heckerman, ...
American journal of respiratory and critical care medicine 181 (11), 1200-1206, 2010
4322010
A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies
O Stegle, L Parts, R Durbin, J Winn
PLoS computational biology 6 (5), e1000770, 2010
3982010
The layout consistent random field for recognizing and segmenting partially occluded objects
J Winn, J Shotton
2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006
3562006
Markov random fields for vision and image processing
A Blake, P Kohli, C Rother
MIT press, 2011
3302011
The 2005 pascal visual object classes challenge
M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ...
Machine Learning Challenges Workshop, 117-176, 2005
3092005
Photo clip art
JF Lalonde, D Hoiem, AA Efros, C Rother, J Winn, A Criminisi
ACM transactions on graphics (TOG) 26 (3), 3-es, 2007
2902007
Discriminative object class models of appearance and shape by correlatons
S Savarese, J Winn, A Criminisi
2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006
2822006
The shape boltzmann machine: a strong model of object shape
SMA Eslami, N Heess, CKI Williams, J Winn
International Journal of Computer Vision 107 (2), 155-176, 2014
2382014
3d layoutcrf for multi-view object class recognition and segmentation
D Hoiem, C Rother, J Winn
2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007
1892007
Tree-based classifiers for bilayer video segmentation
P Yin, A Criminisi, J Winn, I Essa
2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007
1652007
Entangled decision forests and their application for semantic segmentation of CT images
A Montillo, J Shotton, J Winn, JE Iglesias, D Metaxas, A Criminisi
Biennial International Conference on Information Processing in Medical …, 2011
1632011
Infer. NET 2.5
T Minka
http://research. microsoft. com/infernet, 2012
1522012
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