The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search
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Citations
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
Video Google: a text retrieval approach to object matching in videos
Sivic, & Zisserman (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238663 · Cited by 6,367
Robust wide-baseline stereo from maximally stable extremal regions
Matas, J., Chum, O., Urban, M., & Pajdla, T. (2004) · Image and Vision Computing · doi:10.1016/j.imavis.2004.02.006 · Cited by 3,760
Scalable Recognition with a Vocabulary Tree
Nistér, D., & Stewénius, H. (2006) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2006.264 · Cited by 3,641
Scale & Affine Invariant Interest Point Detectors
Mikolajczyk, K., & Schmid, C. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000027790.02288.f2 · Cited by 3,436
Self-citationLocality-sensitive hashing scheme based on p-stable distributions
Datar, M., Immorlica, N., Indyk, P., & Mirrokni, V. (2004) · Annual Symposium on Computational Geometry (SoCG) · doi:10.1145/997817.997857 · Cited by 2,971
Object retrieval with large vocabularies and fast spatial matching
Philbin, J. F., Chum, O., Isard, M., Šivic, J., & Zisserman, A. (2007) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2007.383172 · Cited by 2,931
Lost in quantization: Improving particular object retrieval in large scale image databases
Philbin, J., Chum, O., Isard, M., Sivic, J., & Zisserman, A. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587635 · Cited by 1,478
Robust Wide Baseline Stereo from Maximally Stable Extremal Regions
Matas, J., Chum, O., Urban, M., & Pajdla, T. (2002) · Procedings of the British Machine Vision Conference 2002 · doi:10.5244/c.16.36 · Cited by 1,350
City-Scale Location Recognition
Schindler, G., Brown, M., & Szeliski, R. (2007) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2007.383150 · Cited by 622
Cited by
Sorted by citations
Scalable Person Re-identification: A Benchmark
Zheng, L., Shen, L., Tian, L., Wang, S., Wang, J., & Tian, Q. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.133 · Cited by 4,787
“In the last decade, a myriad of methods [15, 42, 45] have been developed to improve search performance.”
MethodCNN Features Off-the-Shelf: An Astounding Baseline for Recognition
Razavian, A. S., Azizpour, H., Sullivan, J., & Carlsson, S. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2014.131 · Cited by 4,451
Product Quantization for Nearest Neighbor Search
Jégou, H., Douze, M., & Schmid, C. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.57 · Cited by 2,956
“Comparison with Hamming embedding methods: We compare our approach to spectral hashing (SH) [19], which maps vectors to binary signatures.”
MethodInfluentialSelf-citationAggregating local descriptors into a compact image representation
Jeǵou, H., Douze, M., Schmid, C., & Pérez, P. (2010) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2010.5540039 · Cited by 2,679
“VLAD k=16 VLAD k=64 VLAD k=256 miniBOF [8] miniBOF 1 miniBOF 4 miniBOF 8 miniBOF 16 miniBOF 32”
BackgroundSelf-citationNetVLAD: CNN Architecture for Weakly Supervised Place Recognition
Arandjelović, R., Gronát, P., Torii, A., Pajdla, T., & Šivic, J. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/cvpr.2016.572 · Cited by 3,532
“roves over current state-of-the-art compact image representations on standard image retrieval benchmarks. 1.1. Related work While there have been many improvements in designing better image retrieval [2,3,11,12,17,25,26,27,29, 32,48,51,52,53,54,71,78,79,82] and place recognition [4,9,10,15,16,24,35,44,46,63,64,65,75,8…”
BackgroundInfluential
Metadata
- Authors
- Jegou, H., Douze, M., & Schmid, C.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2008
- Volume
- 5302
- Pages
- 304-317
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1556531089
- Semantic Scholar
- 5a2bfaa724ba37134eb55c29644f8576c3d64c96
- Cited by
- 1,901
- References
- 16
- Citations by year
- 2026: 11 · 2025: 22 · 2024: 42 · 2023: 42 · 2022: 72 · 2021: 83 · 2020: 105 · 2019: 130 · 2018: 163 · 2017: 169 · 2016: 192 · 2015: 210 · 2014: 180 · 2013: 144 · 2012: 104
- FWCI
- 61.94
- Type
- conference paper
- Language
- en
- Open access
- green
- inria.hal.science
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- HAL (submittedVersion, other-oa)
- Funders
- Agence Nationale de la Recherche (ANR-07-RIAM-0007, ANR-07-BLAN-0328)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Keywords
- large-scale image search, bag of visual words, approximate nearest neighbor search, binary signatures, visual words, descriptor matching, inverted index, re-ranking, geometric transformation estimation, image retrieval
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