Multi-view complementary hash tables for nearest neighbor search

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2015 International Conference on Computer Vision, ICCV 2015, Issue , 2015, Pages 1107-1115

  Liu, Xianglong ^a   Huang, Lei ^a   Deng, Cheng ^b   Lu, Jiwen ^c   Lang, Bo ^a  

^a BEIHANG UNIVERSITY   (China)

^b XIDIAN UNIVERSITY   (China)

^c TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; DATA STRUCTURES; HASH FUNCTIONS; IMAGE MATCHING;

DATA SIMILARITY; FAST NEAREST NEIGHBOR SEARCH; HASHING TECHNIQUES; LARGE-SCALE IMAGE DATASETS; LOW-RANK MATRICES; OUT-OF-SAMPLE EXTENSION; RANK SIMILARITIES; STATE OF THE ART;

NEAREST NEIGHBOR SEARCH;

EID: 84973901375     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2015.132     Document Type: Conference Paper

References (40)

1. J. Cheng, C. Leng, J. Wu, H. Cui, and H. Lu. Fast and accurate image matching with cascade hashing for 3d reconstruction. In IEEE CVPR, pages 4321-4328, 2014.
2. T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y. Zheng. Nus-wide: A real-world web image database from national university of singapore. In ACM CIVR, 2009.
3. M. Datar, N. Immorlica, P. Indyk, and V. S. Mirrokni. Locality-sensitive hashing scheme based on p-stable distributions. In SCG, pages 253-262, 2004.
4. T. Dean, M. Ruzon, M. Segal, J. Shlens, S. Vijayanarasimhan, and J. Yagnik. Fast, accurate detection of 100, 000 object classes on a single machine. In IEEE CVPR, pages 1-8, 2013.
5. C. Deng, R. Ji, W. Liu, X. Gao, and D. Tao. Visual reranking through weakly supervised multi-graph learning. 2013.
6. J. Friedman, T. Hastie, and R. Tibshirani. Additive logistic regression: A statistical view of boosting. Annals of Statistics, 28:2000, 1998.
7. A. Gionis, P. Indyk, and R. Motwani. Similarity search in high dimensions via hashing. In VLDB, pages 518-529, 1999.
8. Y. Gong, S. Kumar, H. A. Rowley, and S. Lazebnik. Learning binary codes for high-dimensional data using bilinear projections. In IEEE CVPR, 2013.
9. Y. Gong and S. Lazebnik. Iterative quantization: A procrustean approach to learning binary codes. In IEEE CVPR, pages 817-824, june 2011.
10. J. He, S.-F. Chang, R. Radhakrishnan, and C. Bauer. Compact hashing with joint optimization of search accuracy and time. In IEEE CVPR, pages 753-760, 2011.
11. J. He, J. Feng, X. Liu, T. Cheng, T.-H. Lin, H. Chung, and S.-F. Chang. Mobile product search with bag of hash bits and boundary reranking. In IEEE CVPR, pages 3005-3012, 2012.
12. K. He, F. Wen, and J. Sun. K-means hashing: An affinitypreserving quantization method for learning binary compact codes. In IEEE CVPR, pages 2938-2945, June 2013.
13. J.-P. Heo, Y. Lee, J. He, S.-F. Chang, and S.-E. Yoon. Spherical hashing. In IEEE CVPR, pages 2957-2964, 2012.
14. P. Indyk and R. Motwani. Approximate nearest neighbors: Towards removing the curse of dimensionality. In ACM STOC, pages 604-613, 1998.
15. B. Kulis and T. Darrell. Learning to hash with binary reconstructive embeddings. In NIPS, pages 1-8, 2009.
16. S. Kumar and R. Udupa. Learning hash functions for crossview similarity search. In IJCAI, pages 1360-1365, 2011.
17. X. Li, G. Lin, C. Shen, A. Van De n Hengel, and A. Dick. Learning hash functions using column generation. In ICML, 2013.
18. W. Liu, J. He, and S.-F. Chang. Large graph construction for scalable semi-supervised learning. In ICML, pages 679-686, 2010.
19. W. Liu, J. Wang, S. Kumar, and S.-F. Chang. Hashing with graphs. In ICML, pages 1-8, 2011.
20. X. Liu, J. He, C. Deng, and B. Lang. Collaborative hashin. In IEEE CVPR, June 2014.
21. X. Liu, J. He, and B. Lang. Reciprocal Hash Tables for Nearest Neighbor Search. In AAAI, pages 626-632, Bellevue, Washington, 2013.
22. X. Liu, J. He, and B. Lang. Multiple feature kernel hashing for large-scale visual search. Pattern Recognition, 47(2):748-757, 2014.
23. X. Liu, J. He, B. Lang, and S.-F. Chang. Hash bit selection: A unified solution for selection problems in hashing. In IEEE CVPR, 2013.
24. Q. Lv, W. Josephson, Z. Wang, M. Charikar, and K. Li. Multi-probe lsh: efficient indexing for high-dimensional similarity search. In VLDB, pages 950-961, 2007.
25. Y. Mu, G. Hua, W. Fan, and S.-F. Chang. Hash-SVM: Scalable kernel machines for large-scale visual classification. In IEEE CVPR, June 2014.
26. M. Norouzi and D. J. Fleet. Cartesian k-means. In IEEE CVPR, pages 2938-2945, June 2013.
27. M. Norouzi, A. Punjani, and D. J. Fleet. Fast search in hamming space with multi-index hashing. In IEEE CVPR, pages 3108-3115, 2012.
28. F. Shen, W. Liu, S. Zhang, Y. Yang, and H. T. Shen. Learning binary codes for maximum inner product search. In IEEE ICCV, 2015.
29. F. Shen, C. Shen, W. Liu, and H. Tao Shen. Supervised discrete hashing. In IEEE CVPR, pages 37-45, June 2015.
30. F. Shen, C. Shen, Q. Shi, A. Van De n Hengel, and Z. Tang. Inductive hashing on manifolds. In IEEE CVPR, Oregon, USA, 2013.
31. M. Slaney, Y. Lifshits, and J. He. Optimal parameters for locality-sensitive hashing. Proceedings of the IEEE, 100(9):634-640, 2012.
32. J. Song, Y. Yang, Z. Huang, H. T. Shen, and R. Hong. Multiple feature hashing for real-time large scale near-duplicate video retrieval. In ACM MM, pages 423-432, 2011.
33. J. Wang, S. Kumar, and S.-F. Chang. Semi-supervised hashing for scalable image retrieval. In IEEE CVPR, pages 3424-3431, 2010.
34. J. Wang, W. Liu, A. Sun, and Y.-G. Jiang. Learning hash codes with listwise supervision. In IEEE ICCV, pages 3032-3039, 2013.
35. Y. Weiss, A. Torralba, and R. Fergus. Spectral hashing. In NIPS, pages 1-8, 2008.
36. Y. Xia, K. He, P. Kohli, and J. Sun. Sparse projections for high-dimensional binary codes. In IEEE CVPR, 2015.
37. H. Xu, J. Wang, Z. Li, G. Zeng, S. Li, and N. Yu. Complementary hashing for approximate nearest neighbor search. In IEEE ICCV, pages 1631-1638, 2011.
38. G. Ye, D. Liu, J. Wang, and S.-F. Chang. Large-scale video hashing via structure learning. In IEEE ICCV, 2013.
39. F. Yu, R. Ji, M.-H. Tsai, G. Ye, and S.-F. Chang. Weak attributes for large-scale image retrieval. In IEEE CVPR, pages 2949-2956, 2012.
40. X. Yu, S. Kumar, Y. Gong, and S. Chang. Circulant binary embedding. In ICML, 2014.