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Understanding Scenes on Many Levels. J. Tighe and S. Lazebnik. Proceedings of the IEEE International Conference on Computer Vision, 2011. |
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Scene Recognition and Weakly Supervised Object Localization with Deformable Part-Based Models. M. Pandey and S. Lazebnik. Proceedings of the IEEE International Conference on Computer Vision, 2011. Project webpage. |
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Iterative Quantization: A Procrustean Approach to Learning Binary Codes. Y. Gong and S. Lazebnik. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2011. Project webpage. |
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Comparing Data-Dependent and Data-Independent Embeddings for Classification and Ranking of Internet Images. Y. Gong and S. Lazebnik. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2011. Project webpage. |
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Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs. R. Raguram, C. Wu, J.-M. Frahm, and S. Lazebnik. International Journal of Computer Vision, vol. 95, no. 3, December 2011, pp. 213-239. Project webpage. |
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SuperParsing: Scalable Nonparametric Image Parsing with Superpixels. J. Tighe and S. Lazebnik. Proceedings of the European Conference on Computer Vision, 2010. Project webpage, code, poster. |
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Building Rome on a Cloudless Day. J.-M. Frahm, P. Georgel, D. Gallup, T. Johnson, R. Raguram, C. Wu, Y.-H. Jen, E. Dunn, B. Clipp, S. Lazebnik, and M. Pollefeys. Proceedings of the European Conference on Computer Vision, 2010. Project webpage, video, UNC spotlight. |
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Fast Robust Large-scale Mapping from Video and Internet Photo Collections. J.-M. Frahm, M. Pollefeys, S. Lazebnik, C. Zach, D. Gallup, B. Clipp, R. Raguram, C. Wu, and T. Johnson. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 65, no. 6 (special issue on 100 years of ISPRS), 2010, pp. 538-549. |
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Fast Robust Reconstruction of Large Scale Environments. J.-M. Frahm, M. Pollefeys, S. Lazebnik, B. Clipp, D. Gallup, R. Raguram, and C. Wu. Conference on Information Sciences and Systems (CISS), 2010. |
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Near-Minimax Recursive Density Estimation on the Binary Hypercube. M. Raginsky, S. Lazebnik, R. Willett, and J. Silva. Advances in Neural Information Processing Systems, 2008. |
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Analysis of Human Attractiveness Using Manifold Kernel Regression. B. Davis and S. Lazebnik. Proceedings of the IEEE International Conference on Image Processing (Special Session on Aesthetics, Mood, and Emotion), 2008. |
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Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs. X. Li, C. Wu, C. Zach, S. Lazebnik and J.-M. Frahm. Proceedings of the European Conference on Computer Vision, 2008. Project webpage, data, poster. |
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Computing Iconic Summaries for General Visual Concepts. R. Raguram and S. Lazebnik. First IEEE Workshop on Internet Vision (held in conjunction with CVPR), 2008. |
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Learning Nearest-Neighbor Quantizers from Labeled Data by Information Loss Minimization. S. Lazebnik and M. Raginsky. International Conference on Artificial Intelligence and Statistics, 2007. |
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Projective Visual Hulls. S. Lazebnik, Y. Furukawa, and J. Ponce. International Journal of Computer Vision, vol. 74, no. 2, August 2007, pp. 137-165. Visual hull datasets. |
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Segmenting, Modeling, and Matching Video Clips Containing Multiple Moving Objects. F. Rothganger, S. Lazebnik, C. Schmid, and J. Ponce. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 3, March 2007, pp. 477-491. |
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Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study. J. Zhang, M. Marszalek, S. Lazebnik, and C. Schmid. International Journal of Computer Vision, vol. 73, no. 2, June 2007, pp. 213-238. |
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Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories. S. Lazebnik, C. Schmid, and J. Ponce. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, New York, June 2006, vol. II, pp. 2169-2178. MATLAB code, 15 scene category dataset. |
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Local, Semi-Local and Global Models for Texture, Object and Scene Recognition. S. Lazebnik. Ph.D. Dissertation, May 2006 (also Beckman CVR Technical Report 2006-01). Defense slides. |
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3D Object Modeling and Recognition Using Local Affine-Invariant Image Descriptors and Multi-View Spatial Constraints. F. Rothganger, S. Lazebnik, C. Schmid, and J. Ponce. International Journal of Computer Vision, vol. 66, no. 3, March 2006, pp. 231-259. |
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Dataset Issues in Object Recognition. J. Ponce, T. L. Berg, M. Everingham, D. A. Forsyth, M. Hebert, S. Lazebnik, M. Marszalek, C. Schmid, B. C. Russell, A. Torralba, C. K. I. Williams, J. Zhang, and A. Zisserman. Toward Category-Level Object Recognition, Springer-Verlag Lecture Notes in Computer Science vol. 4170. J. Ponce, M. Hebert, C. Schmid, and A. Zisserman (eds.), 2006, pp. 29-48. |
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A Discriminative Framework for Texture and Object Recognition Using Local Image Features. S. Lazebnik, C. Schmid, and J. Ponce. Toward Category-Level Object Recognition, Springer-Verlag Lecture Notes in Computer Science vol. 4170. J. Ponce, M. Hebert, C. Schmid, and A. Zisserman (eds.), 2006, pp. 423-442. |
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3D Object Modeling and Recognition from Photographs and Image Sequences. F. Rothganger, S. Lazebnik, C. Schmid, and J. Ponce. Toward Category-Level Object Recognition, Springer-Verlag Lecture Notes in Computer Science vol. 4170. J. Ponce, M. Hebert, C. Schmid, and A. Zisserman (eds.), 2006, pp. 105-126. |
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Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization. M. Raginsky and S. Lazebnik. Advances in Neural Information Processing Systems 18, MIT Press, 2005, pp. 1105-1112. |
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A Maximum Entropy Framework for Part-Based Texture and Object Recognition. S. Lazebnik, C. Schmid, and J. Ponce. Proceedings of the IEEE International Conference on Computer Vision, Beijing, China, October 2005, vol. 1, pp. 832-838. |
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A Sparse Texture Representation Using Local Affine Regions. S. Lazebnik, C. Schmid, and J. Ponce. IEEE Transactions on Pattern Analysis and Machine Intelligence, August 2005, vol. 27, no. 8, pp. 1265-1278. UIUC texture dataset. |
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The Local Projective Shape of Smooth Surfaces and Their Outlines. S. Lazebnik and J. Ponce. International Journal of Computer Vision, June 2005, vol. 63, no. 1, pp. 65-83. |
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Pattern Recognition with Local Invariant Features. C. Schmid, G. Dorko, S. Lazebnik, K. Mikolajczyk, and J. Ponce. Handbook of Pattern Recognition and Computer Vision, 3rd edition. C.H. Chen and P.S.P Wang editors, World Scientific Publishing Co., 2005, pp. 71-92. |