Publication list [text only]
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Multi-Level Active Prediction of Useful Image Annotations for Recognition. S. Vijayanarasimhan
and K. Grauman. To appear,
Advances in Neural Information
Processing Systems (NIPS), |
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Online Metric Learning and Fast Similarity
Search. P. Jain, B. Kulis, |
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Fast
Image Search for Learned Metrics. P.
Jain, B. Kulis, and K. Grauman. In Proceedings
of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
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Keywords
to Visual Categories: Multiple-Instance Learning for Weakly Supervised Object
Categorization. S. Vijayanarasimhan
and K. Grauman. In Proceedings of the IEEE Conference on
Computer Vision and Pattern Recognition (CVPR), |
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Foreground
Focus: Finding Meaningful Features in Unlabeled Images. Y. J. Lee and K.
Grauman. In Proceedings of the
British Machine Vision Conference (BMVC), |
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Watch, Listen &
Learn: Co-training on Captioned Images and Videos. S. Gupta, J. Kim, K. Grauman, and R.
Mooney. To appear, Proceedings of
the European Conference on Machine Learning and Principles and Practice of
Knowledge Discovery in Databases (ECML), Antwerp, Belgium, September
2008. [pdf] [ppt] |
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Active Learning
with Gaussian Processes for Object Categorization. A. Kapoor, K.
Grauman, R. Urtasun, and T. Darrell. In Proceedings
of the IEEE International Conference on Computer Vision, |
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Pyramid Match Kernel |
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Pyramid Match Kernel: Discriminative Classification with Sets of Image
Features. K. Grauman and T.
Darrell. In Proceedings of the IEEE International Conference on
Computer Vision (ICCV), The
Pyramid Match: Efficient Learning with Partial Correspondences. K. Grauman. In Proceedings
of the Association for the Advancement of Artificial Intelligence (AAAI),
Nectar track, The Pyramid
Match Kernel: Efficient Learning with Sets of Features. K. Grauman and T. Darrell. Journal
of Machine Learning Research (JMLR), 8 (Apr): 725--760, 2007. [pdf] [project
page] [code] K. Grauman. Matching Sets of Features for Efficient
Retrieval and Recognition, Ph.D. Thesis, MIT, 2006. [pdf] (35.8 MB) |
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Pyramid
Match Hashing: Sub-Linear Time Indexing Over Partial Correspondences. K. Grauman and T. Darrell. In Proceedings
of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
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Approximate
Correspondences in High Dimensions. K. Grauman
and T. Darrell. In Advances in Neural
Information Processing Systems 19 (NIPS) 2007. [ps] [pdf] [code] [poster
(pdf)]
[poster
(ppt)] |
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Unsupervised
Learning of Categories from Sets of Partially Matching Image Features. K. Grauman and T. Darrell. In Proceedings
of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
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Efficient Image Matching
with Distributions of Local Invariant Features. K. Grauman and T. Darrell. In
Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Fast
Contour Matching Using Approximate Earth Mover's Distance. K.
Grauman and T. Darrell. In Proceedings
of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), |
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A Picture is Worth a
Thousand Keywords: Image-Based Object Search on a Mobile Platform. T. Yeh, K. Grauman, K. Tollmar,
and T. Darrell. In CHI 2005, Conference on Human Factors in
Computing Systems, |
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Inferring
3D Structure with a Statistical Image-Based Shape Model. K.
Grauman, G. Shakhnarovich, and T. Darrell. In
Proceedings of the IEEE International Conference on Computer Vision (ICCV), Nice, K. Grauman. A
Statistical Image-Based Shape Model for Visual Avoiding
the ``Streetlight Effect'': Tracking by Exploring Likelihood Modes. D. Demirdjian, L.
Taycher, G. Shakhnarovich,
K. Grauman, and T. Darrell. In Proceedings
of the IEEE International Conference on Computer Vision (ICCV), |
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A
Bayesian Approach to Image-Based Visual Hull Reconstruction. K. Grauman, G. Shakhnarovich,
and T. Darrell. In Proceedings of
the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Virtual Visual Hulls: Example-Based 3D Shape Inference from a Single Silhouette. K. Grauman, G. Shakhnarovich, and T. Darrell. In Proceedings of the 2nd Workshop on Statistical Methods in Video Processing, in conjunction with ECCV, Prague, Czech Republic, May 2004. [pdf] [SpringerLink] |
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Communication
via Eye Blinks and Eyebrow Raises: Video-Based Human-Computer Interfaces.
K. Grauman, M. Betke, J. Lombardi, J. Gips, and G. Bradski. Universal
Access in the Information Society, 2(4) pp. 359-373, Springer-Verlag Communication
via Eye Blinks: Detection and Duration Analysis in Real Time. K. Grauman, M. Betke,
J. Gips, and G. Bradski.
In Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition (CVPR), |
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