PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Andrew Zisserman

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Number of EPrints submitted by this user: 10

Extending Pictorial Structures for Object Recognition
M. Pawan Kumar, Philip Torr and Andrew Zisserman
In: BMVC 2004, Kingston, UK(2004).

Trainable visual models for object class recognition
Andrew Zisserman
In: Pascal Pattern Recognition and Machine Learning in Computer Vision Workshop, 3 - 5 May 2004, Grenoble, France.

Learning Layered Pictorial Structures from Video
M. Pawan Kumar, Philip Torr and Andrew Zisserman
In: ICVGIP 2004, Calcutta, India(2004).

The 2005 PASCAL Visual Object Classes Challenge
Mark Everingham, Andrew Zisserman, Christopher Williams, Luc Van Gool, Moray Allan, Chris Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyorgy Dorko, Stefan Duffner, Jan Eichhorn, Jason Farquhar, Mario Fritz, Christophe Garcia, Tom Griffiths, Frederic Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos Storkey, Sandor Szedmak, William Triggs, Ilkay Ulusoy, Ville Viitaniemi and Jianguo Zhang
In: Selected Proceedings of the first PASCAL Challenges Workshop LNAI . (2006) Springer .

Scene Classification Using a Hybrid Generative/Discriminative Approach
Anna Bosch, Andrew Zisserman and X. Munoz
IEEE Transactions on Pattern Analysis and Machine Intelligence 2008.

Learning Layered Motion Segmentations of Video
Mudigonda Pawan Kumar, Philip Torr and Andrew Zisserman
International Journal of Computer Vision 2008.

Geometric LDA: A Generative Model for Particular Object Discovery
James Philbin, Josef Sivic and Andrew Zisserman
In: Proceedings of the British Machine Vision Conference(2008).

Unsupervised Discovery of Visual Object Class Hierarchies
Josef Sivic, B. Russell, Andrew Zisserman, W. T. Freeman and A. A. Efros
In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition(2008).

An Analysis of Convex Relaxations for MAP Estimation of Discrete MRFs
Mudigonda Pawan Kumar, V. Kolmogorov and Philip Torr
Journal of Machine Learning Research Volume 10, pp. 71-106, 2009.

Improved Moves for Truncated Convex Models
Mudigonda Pawan Kumar and Philip Torr
In: NIPS 22, Neural Information Processing Conference,(2008).