Efficient diffusion on region manifolds: Recovering small objects with compact CNN representations

Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017

Volumn 2017-January, Issue , 2017, Pages 926-935

  Iscen, Ahmet ^a   Tolias, Giorgos ^b   Avrithis, Yannis ^a   Furon, Teddy ^a   Chum, Ondřej ^b  

^a INRIA   (France)

^b CZECH TECHNICAL UNIVERSITY IN PRAGUE   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; COMPUTER VISION; DIFFUSION; IMAGE ENHANCEMENT; LINEAR SYSTEMS;

FEATURE SPACE; IMAGE DESCRIPTOR; IMAGE MANIFOLDS; IMAGE SIMILARITY; OVERLAPPING IMAGES; QUERY EXPANSION; SMALL OBJECTS; SPARSE LINEAR SYSTEMS;

IMAGE RETRIEVAL;

EID: 85021832357     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.105     Document Type: Conference Paper

References (64)

1. R. Arandjelović, P. Gronat, A. Torii, T. Pajdla, and J. Sivic. NetVLAD: CNN architecture for weakly supervised place recognition. In CVPR, 2016. 1, 7
2. R. Arandjelovic and A. Zisserman. Three things everyone should know to improve object retrieval. In CVPR, June 2012. 2
3. H. Azizpour, A. S. Razavian, J. Sullivan, A. Maki, and S. Carlsson. From generic to specific deep representations for visual recognition. In CVPRW, 2014. 1
4. A. Babenko and V. Lempitsky. Aggregating deep convolutional features for image retrieval. In ICCV, 2015. 1, 4
5. A. Babenko and V. Lempitsky. Efficient indexing of billion-scale datasets of deep descriptors. In CVPR, 2016. 1, 4, 6
6. S. Chen, L. Zheng, X. Hu, and P. Zhou. Discriminative saliency propagation with sink points. Pattern recognition, 60:2-12, 2016. 2
7. O. Chum, A. Mikulik, M. Perdoch, and J. Matas. Total recall II: Query expansion revisited. In CVPR, June 2011. 2
8. O. Chum, J. Philbin, J. Sivic, M. Isard, and A. Zisserman. Total recall: Automatic query expansion with a generative feature model for object retrieval. In ICCV, October 2007. 1, 2, 7, 8
9. F. R. Chung. Spectral graph theory, volume 92. American Mathematical Soc., 1997. 3
10. A. Delvinioti, H. Jégou, L. Amsaleg, and M. Houle. Image retrieval with reciprocal and shared nearest neighbors. In VISAPP, 2014. 2
11. W. Dong, M. Charikar, and K. Li. Efficient k-nearest neighbor graph construction for generic similarity measures. In WWW, March 2011. 5, 7
12. M. Donoser. Replicator graph clustering. In BMVC, 2013. 2
13. M. Donoser and H. Bischof. Diffusion processes for retrieval revisited. In CVPR, 2013. 2, 3, 5
14. A. Egozi, Y. Keller, and H. Guterman. Improving shape retrieval by spectral matching and meta similarity. IEEE Transactions on Image Processing, 19(5):1319-1327, 2010. 2
15. T. Furuya and R. Ohbuchi. Diffusion-on-manifold aggregation of local features for shape-based 3d model retrieval. In ICMR, 2015. 2
16. Z. Gao, J. Xue, W. Zhou, S. Pang, and Q. Tian. Democratic diffusion aggregation for image retrieval. IEEE Trans. on Multimedia, 18:1661 - 1674, 2016. 2
17. Y. Gong, L. Wang, R. Guo, and S. Lazebnik. Multi-scale orderless pooling of deep convolutional activation features. In ECCV, 2014. 4
18. A. Gordo, J. Almazan, J. Revaud, and D. Larlus. Deep image retrieval: Learning global representations for image search. ECCV, 2016. 1, 8
19. A. Gordo, J. Almazan, J. Revaud, and D. Larlus. End-to-end learning of deep visual representations for image retrieval. In arXiv, 2016. 1, 6, 7
20. L. Grady. Random walks for image segmentation. IEEE Trans. PAMI, 28(11):1768-1783, 2006. 2, 3, 4, 5
21. W. Hackbusch. Iterative solution of large sparse systems of equations. Springer Verlag, 1994. 5
22. J. Heinly, J. L. Schonberger, E. Dunn, and J.-M. Frahm. Reconstructing the world* in six days*(as captured by the yahoo 100 million image dataset). In CVPR, 2015. 1
23. A. Iscen, T. Furon, V. Gripon, M. Rabbat, and H. Jégou. Memory vectors for similarity search in high-dimensional spaces. In arXiv, 2014. 4
24. A. Iscen, M. Rabbat, and T. Furon. Efficient large-scale similarity search using matrix factorization. In CVPR, 2016. 6
25. H. Jégou, M. Douze, and C. Schmid. Product quantization for nearest neighbor search. IEEE Trans. PAMI, 33(1):117-128, January 2011. 1, 6
26. H. Jégou, M. Douze, C. Schmid, and P. Pérez. Aggregating local descriptors into a compact image representation. In CVPR, June 2010. 1
27. H. Jégou, H. Harzallah, and C. Schmid. A contextual dissimilarity measure for accurate and efficient image search. In CVPR, 2007. 2
28. Y. Jing and S. Baluja. Visualrank: Applying pagerank to large-scale image search. IEEE Trans. PAMI, 30(11):1877-1890, 2008. 2
29. Y. Kalantidis and Y. Avrithis. Locally optimized product quantization for approximate nearest neighbor search. In CVPR, 2014. 1, 6
30. Y. Kalantidis, C. Mellina, and S. Osindero. Cross-dimensional weighting for aggregated deep convolutional features. In ECCVW, 2016. 1, 4, 7, 8
31. P. Kontschieder, M. Donoser, and H. Bischof. Beyond pairwise shape similarity analysis. In ACCV, 2009. 3
32. A. N. Langville and C. D. Meyer. Deeper inside pagerank. Internet Mathematics, 1(3):335-380, 2004. 5
33. S. Lu, V. Mahadevan, and N. Vasconcelos. Learning optimal seeds for diffusion-based salient object detection. In CVPR, 2014. 2
34. A. Mikulik, O. Chum, and J. Matas. Image retrieval for online browsing in large image collections. In International Conference on Similarity Search and Applications, 2013. 1
35. K. R. Mopuri and R. V. Babu. Object level deep feature pooling for compact image representation. CVPRW, 2015. 1
36. M. Muja and D. G. Lowe. Scalable nearest neighbor algorithms for high dimensional data. IEEE Trans. PAMI, 36, 2014. 1, 6
37. N. Murray and F. Perronnin. Generalized max-pooling. In CVPR, June 2014. 4
38. J. Nocedal and S. Wright. Numerical optimization. Springer, 2006. 5
39. L. Page, S. Brin, R. Motwani, and T. Winograd. The pagerank citation ranking: bringing order to the web. 1999. 2, 4
40. J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Object retrieval with large vocabularies and fast spatial matching. In CVPR, June 2007. 4, 5
41. J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Lost in quantization: Improving particular object retrieval in large scale image databases. In CVPR, June 2008. 5
42. D. Qin, S. Gammeter, L. Bossard, T. Quack, and L. Van Gool. Hello neighbor: Accurate object retrieval with k-reciprocal nearest neighbors. In CVPR, 2011. 2, 7, 8
43. F. Radenović, G. Tolias, and O. Chum. CNN image retrieval learns from BoW: Unsupervised fine-tuning with hard examples. ECCV, 2016. 4, 6, 7
44. A. S. Razavian, J. Sullivan, S. Carlsson, and A. Maki. Visual instance retrieval with deep convolutional networks. ITE Transactions on Media Technology and Applications, 4:251-258, 2016. 1, 4, 6, 7, 8
45. M. Richardson and P. M. Domingos. The intelligent surfer: Probabilistic combination of link and content information in pagerank. In NIPS, 2001. 2
46. T. Sattler, T. Weyand, B. Leibe, and L. Kobbelt. Image retrieval for image-based localization revisited. In BMVC, 2012. 1
47. J. L. Schonberger, F. Radenovic, O. Chum, and J.-M. Frahm. From single image query to detailed 3d reconstruction. In CVPR, 2015. 1
48. X. Shen, Z. Lin, J. Brandt, and Y. Wu. Spatially-constrained similarity measure for large-scale object retrieval. IEEE Trans. PAMI, 36(6):1229-1241, 2014. 2, 7, 8
49. J. Sivic and A. Zisserman. Video Google: A text retrieval approach to object matching in videos. In ICCV, 2003. 2, 4
50. G. Tolias, Y. Avrithis, and H. Jégou. To aggregate or not to aggregate: Selective match kernels for image search. In ICCV, December 2013. 6
51. G. Tolias and H. Jégou. Visual query expansion with or without geometry: refining local descriptors by feature aggregation. Pattern recognition, 47(10):3466-3476, 2014. 2, 7, 8
52. G. Tolias, R. Sicre, and H. Jégou. Particular object retrieval with integral max-pooling of cnn activations. ICLR, 2016. 1, 4, 6, 7, 8
53. L. N. Trefethen and D. Bau III. Numerical linear algebra. SIAM, 1997. 5
54. N. K. Vishnoi. Laplacian solvers and their algorithmic applications. Theoretical Computer Science, 8(1-2):1-141, 2012. 5
55. S. Wang and S. Jiang. INSTRE: a new benchmark for instance-level object retrieval and recognition. ACM Transactions on Multimedia Computing, Communications, and Applications, 11:37, 2015. 2, 5, 6
56. T. Weyand and B. Leibe. Discovering favorite views of popular places with iconoid shift. In ICCV, 2011. 1
57. L. Xie, R. Hong, B. Zhang, and Q. Tian. Image classification and retrieval are one. In ICMR, 2015. 1
58. L. Xie, Q. Tian, W. Zhou, and B. Zhang. Fast and accurate near-duplicate image search with affinity propagation on the imageweb. CVIU, 124, 2014. 2
59. F. Yang, B. Matei, and L. S. Davis. Re-ranking by multi-feature fusion with diffusion for image retrieval. In WACV, 2015. 2
60. X. Yang, S. Koknar-Tezel, and L. J. Latecki. Locally constrained diffusion process on locally densified distance spaces with applications to shape retrieval. In CVPR, 2009. 2
61. S. Zhang, M. Yang, T. Cour, K. Yu, and D. N. Metaxas. Query specific fusion for image retrieval. In ECCV, 2012. 2, 3
62. W. Zhang, C.-W. Ngo, and X. Cao. Hyperlink-aware object retrieval. IEEE Transactions on Image Processing, 25(9):4186-4198, 2016. 2
63. D. Zhou, O. Bousquet, T. N. Lal, J. Weston, and B. Schölkopf. Learning with local and global consistency. In NIPS, 2003. 2, 3, 5, 6
64. D. Zhou, J. Weston, A. Gretton, O. Bousquet, and B. Schölkopf. Ranking on data manifolds. In NIPS, 2003. 2, 3, 4