LDAHash: Improved Matching with Smaller Descriptors
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Pascal Fua | Alexander M. Bronstein | Christoph Strecha | Michael M. Bronstein | C. Strecha | P. Fua | A. Bronstein | M. Bronstein
[1] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.
[2] Peter L. Bartlett,et al. Boosting Algorithms as Gradient Descent , 1999, NIPS.
[3] Piotr Indyk,et al. Similarity Search in High Dimensions via Hashing , 1999, VLDB.
[4] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[5] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[6] 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..
[7] Ayhan Demiriz,et al. Linear Programming Boosting via Column Generation , 2002, Machine Learning.
[8] George Kollios,et al. BoostMap: A method for efficient approximate similarity rankings , 2004, CVPR 2004.
[9] Mayank Bawa,et al. LSH forest: self-tuning indexes for similarity search , 2005, WWW '05.
[10] Cordelia Schmid,et al. A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.
[11] Cordelia Schmid,et al. A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[12] Kilian Q. Weinberger,et al. Distance Metric Learning for Large Margin Nearest Neighbor Classification , 2005, NIPS.
[13] Gregory Shakhnarovich,et al. Learning task-specific similarity , 2005 .
[14] Steven M. Seitz,et al. Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..
[15] Gang Hua,et al. Discriminant Embedding for Local Image Descriptors , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[16] Jiri Matas,et al. Improving Descriptors for Fast Tree Matching by Optimal Linear Projection , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[17] Cordelia Schmid,et al. Vector Quantizing Feature Space with a Regular Lattice , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[18] Matthew A. Brown,et al. Learning Local Image Descriptors , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[19] A. Vedaldi. An open implementation of the SIFT detector and descriptor , 2007 .
[20] Cordelia Schmid,et al. Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search , 2008, ECCV.
[21] Prateek Jain,et al. Fast image search for learned metrics , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[22] 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 .
[23] Antonio Torralba,et al. Spectral Hashing , 2008, NIPS.
[24] Antonio Torralba,et al. Small codes and large image databases for recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[25] Luc Van Gool,et al. Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..
[26] Pascal Fua,et al. On benchmarking camera calibration and multi-view stereo for high resolution imagery , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[27] Sam S. Tsai,et al. CHoG: Compressed histogram of gradients A low bit-rate feature descriptor , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[28] Svetlana Lazebnik,et al. Locality-sensitive binary codes from shift-invariant kernels , 2009, NIPS.
[29] Lei Wang,et al. Positive Semidefinite Metric Learning with Boosting , 2009, NIPS.
[30] Cordelia Schmid,et al. Packing bag-of-features , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[31] Christopher Hunt,et al. Notes on the OpenSURF Library , 2009 .
[32] Trevor Darrell,et al. Learning to Hash with Binary Reconstructive Embeddings , 2009, NIPS.
[33] Matthew A. Brown,et al. Picking the best DAISY , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[34] Vincent Lepetit,et al. BRIEF: Binary Robust Independent Elementary Features , 2010, ECCV.
[35] Alexander M. Bronstein,et al. The Video Genome , 2010, ArXiv.
[36] Vincent Lepetit,et al. DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[37] Pascal Fua,et al. Dynamic and scalable large scale image reconstruction , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[38] Leonidas J. Guibas,et al. Image webs: Computing and exploiting connectivity in image collections , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[39] Shih-Fu Chang,et al. Sequential Projection Learning for Hashing with Compact Codes , 2010, ICML.
[40] Shih-Fu Chang,et al. Semi-supervised hashing for scalable image retrieval , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[41] Nikos Paragios,et al. Data fusion through cross-modality metric learning using similarity-sensitive hashing , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[42] Leonidas J. Guibas,et al. Shape google: Geometric words and expressions for invariant shape retrieval , 2011, TOGS.
[43] Cordelia Schmid,et al. Product Quantization for Nearest Neighbor Search , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[44] Gang Hua,et al. Discriminative Learning of Local Image Descriptors , 1990, IEEE Transactions on Pattern Analysis and Machine Intelligence.