Fast Similarity Search for Learned Metrics
暂无分享,去创建一个
[1] Piotr Indyk,et al. Low-Dimensional Embedding with Extra Information , 2004, SCG '04.
[2] Donald E. Porter,et al. Improved error reporting for software that uses black-box components , 2007, PLDI '07.
[3] Trevor Darrell,et al. Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (Neural Information Processing) , 2006 .
[4] Kilian Q. Weinberger,et al. Distance Metric Learning for Large Margin Nearest Neighbor Classification , 2005, NIPS.
[5] Matthijs C. Dorst. Distinctive Image Features from Scale-Invariant Keypoints , 2011 .
[6] Cordelia Schmid,et al. Scale & Affine Invariant Interest Point Detectors , 2004, International Journal of Computer Vision.
[7] Nello Cristianini,et al. Learning the Kernel Matrix with Semidefinite Programming , 2002, J. Mach. Learn. Res..
[8] Trevor Darrell,et al. The Pyramid Match Kernel: Efficient Learning with Sets of Features , 2007, J. Mach. Learn. Res..
[9] Trevor Darrell,et al. Pyramid Match Hashing: Sub-Linear Time Indexing Over Partial Correspondences , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[10] Koby Crammer,et al. Kernel Design Using Boosting , 2002, NIPS.
[11] Jitendra Malik,et al. Image Retrieval and Classification Using Local Distance Functions , 2006, NIPS.
[12] George Kollios,et al. BoostMap: A method for efficient approximate similarity rankings , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[13] Antonio Torralba,et al. Ieee Transactions on Pattern Analysis and Machine Intelligence 1 80 Million Tiny Images: a Large Dataset for Non-parametric Object and Scene Recognition , 2022 .
[14] David Nistér,et al. Scalable Recognition with a Vocabulary Tree , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[15] David G. Stork,et al. Pattern Classification , 1973 .
[16] Andrew McCallum,et al. A comparison of event models for naive bayes text classification , 1998, AAAI 1998.
[17] Tomer Hertz,et al. Learning distance functions for image retrieval , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[18] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[19] Trevor Darrell,et al. Approximate Correspondences in High Dimensions , 2006, NIPS.
[20] Andrew Zisserman,et al. Video data mining using configurations of viewpoint invariant regions , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[21] Jon Louis Bentley,et al. An Algorithm for Finding Best Matches in Logarithmic Expected Time , 1977, TOMS.
[22] Ilan Shimshoni,et al. Mean shift based clustering in high dimensions: a texture classification example , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[23] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[24] Stefano Soatto,et al. Proximity Distribution Kernels for Geometric Context in Category Recognition , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[25] Jitendra Malik,et al. SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[26] Pietro Perona,et al. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[27] Jeffrey K. Uhlmann,et al. Satisfying General Proximity/Similarity Queries with Metric Trees , 1991, Inf. Process. Lett..
[28] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[29] Yann LeCun,et al. Dimensionality Reduction by Learning an Invariant Mapping , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[30] Jiri Matas,et al. Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..
[31] Nicole Immorlica,et al. Locality-sensitive hashing scheme based on p-stable distributions , 2004, SCG '04.
[32] Andrew Zisserman,et al. Representing shape with a spatial pyramid kernel , 2007, CIVR '07.
[33] Trevor Darrell,et al. Fast pose estimation with parameter-sensitive hashing , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[34] Steven M. Seitz,et al. Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..
[35] Geoffrey E. Hinton,et al. Neighbourhood Components Analysis , 2004, NIPS.
[36] Prateek Jain,et al. Fast image search for learned metrics , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[37] David G. Lowe,et al. Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration , 2009, VISAPP.
[38] David P. Williamson,et al. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming , 1995, JACM.
[39] Gang Hua,et al. Discriminant Embedding for Local Image Descriptors , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[40] Jitendra Malik,et al. Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[41] Tomer Hertz,et al. Learning a Mahalanobis Metric from Equivalence Constraints , 2005, J. Mach. Learn. Res..
[42] Manik Varma,et al. Learning The Discriminative Power-Invariance Trade-Off , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[43] Trevor Darrell,et al. The pyramid match kernel: discriminative classification with sets of image features , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[44] Trevor Darrell,et al. Conditional Random People: Tracking Humans with CRFs and Grid Filters , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[45] Stan Sclaroff,et al. Estimating 3D hand pose from a cluttered image , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[46] Michael I. Jordan,et al. Distance Metric Learning with Application to Clustering with Side-Information , 2002, NIPS.
[47] Francesca Odone,et al. Building kernels from binary strings for image matching , 2005, IEEE Transactions on Image Processing.
[48] Amir Globerson,et al. Metric Learning by Collapsing Classes , 2005, NIPS.
[49] Shigeo Abe DrEng. Pattern Classification , 2001, Springer London.
[50] Moses Charikar,et al. Similarity estimation techniques from rounding algorithms , 2002, STOC '02.
[51] Thorsten Joachims,et al. Learning a Distance Metric from Relative Comparisons , 2003, NIPS.
[52] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[53] Daphna Weinshall,et al. Learning a kernel function for classification with small training samples , 2006, ICML.
[54] Inderjit S. Dhillon,et al. Information-theoretic metric learning , 2006, ICML '07.
[55] Antonio Torralba,et al. Small codes and large image databases for recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[56] Piotr Indyk,et al. Approximate nearest neighbors: towards removing the curse of dimensionality , 1998, STOC '98.
[57] David G. Lowe,et al. Shape indexing using approximate nearest-neighbour search in high-dimensional spaces , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.