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Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search
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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
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Dumas, T., Roumy, A., & Guillemot, C. M. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2934565 · Cited by 67
Xia, Y., He, K., Wen, F., & Sun, J. Z. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.424 · Cited by 60
Robust Visual Place Recognition with Graph Kernels
Stumm, E. S., Christopher Mei, A., Lacroix, S., Nieto, J. I., Hutter, M., & Siegwart, R. (2016) · 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.2016.491 · Cited by 61
Person Re-identification Meets Image SearchPreprint
Zheng, L., Shen, L., Tian, L., et al. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.02171 · Cited by 63
Secure Image LBP Feature Extraction in Cloud-Based Smart Campus
Xia, Z., Ma, X., Shen, Z., Sun, X., Xiong, N. N., & Jeon, B. (2018) · IEEE Access · doi:10.1109/access.2018.2845456 · Cited by 61
Deep Variational and Structural Hashing
Liong, V. E., Lu, J., Duan, L., & Tan, Y. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2882816 · Cited by 59
Mobile Visual Search: Architectures, Technologies, and the Emerging MPEG Standard
Girod, B., Chandrasekhar, V., Grzeszczuk, R., et al. (2011) · IEEE Multimedia · doi:10.1109/mmul.2011.48 · Cited by 61
PUPPIES: Transformation-Supported Personalized Privacy Preserving Partial Image Sharing
He, J., Liu, B., Kong, D., Bao, X., Wang, N., Jin, H., & Kesidis, G. (2016) · International Conference on Dependable Systems & Networks/Proceedings · doi:10.1109/dsn.2016.40 · Cited by 60
Unsupervised Local Feature Hashing for Image Similarity Search
Liu, L., Yu, M., & Shao, L. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2480966 · Cited by 57
Weakly Supervised Multi-Graph Learning for Robust Image Reranking
Deng, C. D., Ji, R., Tao, D., et al. (2014) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2014.2298841 · Cited by 60
Pedronette, D. C. G., Gonçalves, F. M. F., & Guilherme, I. R. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.05.009 · Cited by 59
Spatially-Constrained Similarity Measurefor Large-Scale Object Retrieval
Shen, X., Lin, Z., Brandt, J., et al. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.237 · Cited by 60
INRIA-LEAR'S Video Copy Detection System.
Douze, M., Gaidon, A., Jeǵou, H., Marszałek, M., & Schmid, C. (2008) · Cited by 64
Self-citationContextual Query Expansion for Image Retrieval
Xie, H., Zhang, Y., Tan, J., Guo, L., & Li, J. (2014) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2014.2305909 · Cited by 57
Efficient retrieval of deformable shape classes using local self-similarities
Chatfield, K., Philbin, J. F., & Zisserman, A. (2009) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2009.5457691 · Cited by 56
Xie, H., Gao, K., Zhang, Y., Tang, S., Li, J., & Liu, Y. (2011) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2011.2167224 · Cited by 57
Hybrid Image-Retrieval Method for Image-Splicing Validation
Pham, N. T., Lee, J. W., Kwon, G., & Park, C. (2019) · Symmetry · doi:10.3390/sym11010083 · Cited by 60
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Zheng, L., Wang, S., Liu, Z., et al. (2015) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2015.2408563 · Cited by 57
Object level deep feature pooling for compact image representation
Mopuri, K. R., & Babu, R. V. (2015) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2015.7301273 · Cited by 62
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Aly, M., Munich, M. E., & Perona, P. (2011) · Cited by 56
\(\mathcal {L}_p\) -Norm IDF for Scalable Image Retrieval
Zheng, L., Wang, S., & Tian, Q. (2014) · IEEE Transactions on Image Processing · doi:10.1109/tip.2014.2329182 · Cited by 56
Nabi, S. T., Kumar, M., Singh, P., Aggarwal, N., & Kumar, K. (2022) · Multimedia Systems · doi:10.1007/s00530-021-00873-8 · Cited by 55
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Singh, A. D., Dixit, A., & Singh, B. K. (2022) · International Conference on Fourth Industrial Revolution Based Technology and Practices (ICFIRTP) · doi:10.1109/icfirtp56122.2022.10059435 · Cited by 57
Partition Min-Hash for Partial Duplicate Image Discovery
Lee, D. C., Ke, Q., & Isard, M. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15549-9_47 · Cited by 55
LAMV: Learning to Align and Match Videos with Kernelized Temporal Layers
Baraldi, L., Douze, M., Cucchiara, R., & Jeǵou, H. (2018) · 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.2018.00814 · Cited by 55
Self-citationA smart atlas for endomicroscopy using automated video retrieval
André, B., Vercauteren, T. K., Buchner, A. M., Wallace, M. B., & Ayache, N. (2011) · Medical Image Analysis · doi:10.1016/j.media.2011.02.003 · Cited by 54
Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking
Pedronette, D. C. G., Valem, L. P., Almeida, J., & Torres, R. D. S. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2920526 · Cited by 55
Parallel search of k-nearest neighbors with synchronous operations
Sismanis, N., Pitsianis, N. P., & Sun, X. (2012) · IEEE High Performance Extreme Computing Conference · doi:10.1109/hpec.2012.6408667 · Cited by 54
Learning Wavefront Coding for Extended Depth of Field Imaging
Akpinar, U., Şahin, E., Meem, M., et al. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3060166 · Cited by 54
Digital Image Steganalysis: Current Methodologies and Future Challenges
Eid, W. M., Alotaibi, S., Alqahtani, H. M., & Saleh, S. Q. (2022) · IEEE Access · doi:10.1109/access.2022.3202905 · Cited by 60
Automated Pruning for Deep Neural Network Compression
Manessi, F., Rozza, A., Bianco, S., Napoletano, P., & Schettini, R. (2018) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2018.8546129 · Cited by 65
Matchable Image Retrieval by Learning from Surface Reconstruction
Shen, T., Luo, Z., Zhou, L., Zhang, R., Zhu, S., Fang, T., & Quan, L. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-20887-5_26 · Cited by 57
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BSIFT: Toward Data-Independent Codebook for Large Scale Image Search
Zhou, W., Li, H., Hong, R., Lu, Y., & Tian, Q. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2389624 · Cited by 53
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İşcen, A., Tolias, G., Gosselin, P.-H., & Jeǵou, H. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2423557 · Cited by 54
Self-citationPoint cloud descriptors for place recognition using sparse visual information
Cieslewski, T., Stumm, E. S., Gawel, A., Bosse, M., Lynen, S., & Siegwart, R. (2016) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2016.7487687 · Cited by 52
Collaborative Index Embedding for Image Retrieval
Zhou, W., Li, H., Sun, J., et al. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2676779 · Cited by 53
On the burstiness of visual elements
Jegou, H., Douze, M., & Schmid, C. (2009) · 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/cvprw.2009.5206609 · Cited by 53
Self-citationScalable Feature Matching by Dual Cascaded Scalar Quantization for Image Retrieval
Zhou, W., Yang, M., Wang, X., Li, H., Lin, Y., & Tian, Q. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2430329 · Cited by 50
A novel adaptive LBP-based descriptor for color image retrieval
Sotoodeh, M., Moosavi, M. R., & Boostani, R. (2019) · Expert Systems with Applications · doi:10.1016/j.eswa.2019.03.020 · Cited by 52
Effective Image Retrieval System Using Dot-Diffused Block Truncation Coding Features
Guo, J.-M., Prasetyo, H., & Wang, N.-J. (2015) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2015.2449234 · Cited by 52
Asymmetric distances for binary embeddings
Gordo, A., & Perronnin, F. (2011) · 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.2011.5995505 · Cited by 49
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Baroffio, L., Cesana, M., Redondi, A. E. C., Tagliasacchi, M., & Tubaro, S. (2014) · IEEE Transactions on Image Processing · doi:10.1109/tip.2014.2312617 · Cited by 51
Scalable face image retrieval with identity-based quantization and multi-reference re-ranking
Wu, Z., Ke, Q., Sun, J. Z., & Shum, H. (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.2010.5539976 · Cited by 52
Distance Encoded Product Quantization
Heo, J., Lin, Z., & Yoon, S. (2014) · 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.2014.274 · Cited by 50
Memory Vectors for Similarity Search in High-Dimensional Spaces
İşcen, A., Furon, T., Gripon, V., et al. (2017) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2017.2677964 · Cited by 52
Self-citationUnsupervised Part-Based Weighting Aggregation of Deep Convolutional Features for Image Retrieval
Xu, J., Shi, C., Qi, C., Wang, C., & Xiao, B. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.12231 · Cited by 60
Fabric Image Retrieval System Using Hierarchical Search Based on Deep Convolutional Neural Network
Xiang, J., Zhang, N., Pan, R., & Gao, W. (2019) · IEEE Access · doi:10.1109/access.2019.2898906 · Cited by 52
Indexing in large scale image collections: Scaling properties and benchmark
Aly, M., Munich, M. E., & Perona, P. (2011) · Proceedings · doi:10.1109/wacv.2011.5711534 · Cited by 51
Mining Compact Bag-of-Patterns for Low Bit Rate Mobile Visual Search
Ji, R., Duan, L., Chen, J., Huang, T., & Gao, W. (2014) · IEEE Transactions on Image Processing · doi:10.1109/tip.2014.2324291 · Cited by 51
Deep Self-taught Hashing for Image Retrieval
Zhou, K., Liu, Y., Song, J., Yan, L., Zou, F., & Shen, F. (2015) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2733373.2806320 · Cited by 51
Image matching in large scale indoor environment
Kang, H., Efros, A. A., Hebert, M., & Takeo Kanade, A. (2009) · 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2009.5204357 · Cited by 58
Towards Good Practices for Image Retrieval Based on CNN Features
Seddati, O., Dupont, S., Mahmoudi, S., & Parian, M. A. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.150 · Cited by 50
Hamming Embedding and Weak Geometry Consistency for Large Scale Image Search - extended version
Jeǵou, H., Douze, M., & Schmid, C. (2008) · HAL · Cited by 46
Self-citationRobust Coverless Image Steganography Based on Neglected Coverless Image Dataset Construction
Zou, L., Li, J., Wan, W., Wu, Q. M. J., & Sun, J. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3194990 · Cited by 54
Fast geometric re-ranking for image-based retrieval
Tsai, S. S., Chen, D., Takacs, G., et al. (2010) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2010.5648942 · Cited by 50
Deep image retrieval: a surveyPreprint
Chen, W., Liu, Y., Wang, W., Bakker, E. M., Georgiou, T., Fieguth, P., Liu, L., & Lew, M. S. (2021) · Leiden Repository (Leiden University) · Cited by 58
Discriminative Multi-View Interactive Image Re-Ranking
Li, J., Xu, C., Yang, W., Sun, C., & Tao, D. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2651379 · Cited by 48
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Zhang, G., Liang, G., Li, W., Fang, J., Wang, J., Geng, Y., & Wang, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-68935-7_1 · Cited by 47
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Román-Rangel, E., Gayol, C. P., Odobez, J., & Gática-Pérez, D. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-010-0387-x · Cited by 49
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Zhou, W., Li, H., Lu, Y., & Tian, Q. C. (2011) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2072298.2072012 · Cited by 52
Reversible data hiding: A contemporary survey of state-of-the-art, opportunities and challenges
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Perronnin, F., Liu, Y., & Renders, J.-M. (2009) · 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.2009.5206505 · Cited by 49
Large-Scale Image Retrieval with Attentive Deep Local FeaturesPreprint
Noh, H., Araújo, A. D. M., Sim, J., et al. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1612.06321 · Cited by 49
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Min, W., Mei, S., Li, Z., & Jiang, S. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.2974326 · Cited by 48
Coherent bag-of audio words model for efficient large-scale video copy detection
Liu, Y., Zhao, W., Ngo, C., et al. (2010) · ACM International Conference on Image and Video Retrieval (CIVR) · doi:10.1145/1816041.1816057 · Cited by 48
Weighted Component Hashing of Binary Aggregated Descriptors for Fast Visual Search
Duan, L., Lin, J., Wang, Z., et al. (2015) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2015.2419973 · Cited by 48
A fast and efficient image retrieval system based on color and texture features
Singh, C., & Kaur, K. P. (2016) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2016.10.002 · Cited by 48
HNIP: Compact Deep Invariant Representations for Video Matching, Localization, and Retrieval
Lin, J., Duan, L., Wang, S., Bai, Y., Lou, Y., Chandrasekhar, V., Huang, T., Kot, A. C., & Gao, W. (2017) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2017.2713410 · Cited by 47
Deep Self-Taught Hashing for Image Retrieval
Liu, Y., Song, J., Zhou, K., Yan, L., Liu, L., Zou, F., & Shao, L. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2822781 · Cited by 48
Is This the Right Place? Geometric-Semantic Pose Verification for Indoor Visual Localization
Taira, H., Rocco, I., Sedlář, J., Okutomi, M., Šivic, J., Pajdla, T., Sattler, T., & Torii, A. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00447 · Cited by 51
Geometrical FLIRT phrases for large scale place recognition in 2D range data
Tipaldi, G. D., Spinello, L., & Burgard, W. (2013) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2013.6630947 · Cited by 47
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Chu, L., Jiang, S., Wang, S., et al. (2013) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2013.2270455 · Cited by 47
An improved Bag-of-Words framework for remote sensing image retrieval in large-scale image databases
Yang, J., Liu, J., & Dai, Q. (2014) · International Journal of Digital Earth · doi:10.1080/17538947.2014.882420 · Cited by 45
Good match exploration using triangle constraint
Guo, X., & Cao, X. (2011) · Pattern Recognition Letters · doi:10.1016/j.patrec.2011.08.021 · Cited by 47
MS-RMAC: Multiscale Regional Maximum Activation of Convolutions for Image Retrieval
Li, Y., Xu, Y., Wang, J., Miao, Z., & Zhang, Y. (2017) · IEEE Signal Processing Letters · doi:10.1109/lsp.2017.2665522 · Cited by 46
Learning Deep Binary Descriptor with Multi-Quantization
Duan, Y., Lu, J., Wang, Z., Feng, J., & Zhou, J. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2858760 · Cited by 47
TDHPPIR: An Efficient Deep Hashing Based Privacy-Preserving Image Retrieval Method
Zhang, C., Zhu, L., Zhang, S., & Yu, W. (2020) · Neurocomputing · doi:10.1016/j.neucom.2019.11.119 · Cited by 46
A Robust Coverless Image Steganography Based on an End-to-End Hash Generation Model
Meng, L., Jiang, X., Zhang, Z., et al. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3232790 · Cited by 46
Oriented pooling for dense and non-dense rotation-invariant features
Zhao, W.-L., Gravier, G., & Jeǵou, H. (2013) · British Machine Vision Conference (BMVC) · doi:10.5244/c.27.99 · Cited by 52
Self-citationProgressive Large Scale-Invariant Image Matching in Scale Space
Zhou, L., Zhu, S., Shen, T., Wang, J., Fang, T., & Quan, L. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.259 · Cited by 43
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Zhang, X., Yu, F. X., Guo, R., Kumar, S., Wang, S., & Chang, S.-F. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.335 · Cited by 43
Unsupervised Semantic-Based Aggregation of Deep Convolutional Features
Xu, J., Wang, C., Qi, C., Shi, C., & Xiao, B. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2867104 · Cited by 47
Coverless image steganography based on DenseNet feature mapping
Liu, Q., Xiang, X., Qin, J., et al. (2020) · EURASIP Journal on Image and Video Processing · doi:10.1186/s13640-020-00521-7 · Cited by 45
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Avrithis, Y., & Kalantidis, Y. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33712-3_2 · Cited by 45
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Ge, T., Ke, Q., & Sun, J. (2013) · British Machine Vision Conference (BMVC) · doi:10.5244/c.27.132 · Cited by 41
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Kang, H., Hebert, M., & Kanade, T. (2011) · International Conference on Computer Vision · doi:10.1109/iccv.2011.6126314 · Cited by 44
Hou, Y., Zhang, H., & Zhou, S. (2017) · Autonomous Robots · doi:10.1007/s10514-017-9684-3 · Cited by 40
Douze, M., Jeǵou, H., & Perronnin, F. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46475-6_48 · Cited by 46
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Groen, I. I. A., Jahfari, S., Seijdel, N., Ghebreab, S., Lamme, V. A. F., & Scholte, H. S. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006690 · Cited by 37
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Zhang, B., Wang, Z., Gao, J., Rutjes, C., Nufer, K. L., Tao, D., Feng, D. D., & Menzies, S. W. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.3037761 · Cited by 49
On-the-fly learning for visual search of large-scale image and video datasets
Chatfield, K., Arandjelović, R., Parkhi, O., & Zisserman, A. (2015) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-015-0077-0 · Cited by 42
Discrete Cosine Transform Locality-Sensitive Hashes for Face Retrieval
Kafai, M., Eshghi, K., & Bhanu, B. (2014) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2014.2305633 · Cited by 43
Madan, S. K., & Dana, K. (2015) · Pattern Analysis and Applications · doi:10.1007/s10044-015-0472-4 · Cited by 44
Scalable Object Retrieval with Compact Image Representation from Generic Object Regions
Sun, S., Zhou, W., Tian, Q., & Li, H. (2015) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/2818708 · Cited by 42
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Liu, H., Lu, H., & Xue, X. (2012) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2012.92 · Cited by 44
A multi-sample, multi-tree approach to bag-of-words image representation for image retrieval
Wu, Z., Ke, Q., Sun, J., & Shum, H. (2009) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2009.5459439 · Cited by 42
Query-Adaptive Asymmetrical Dissimilarities for Visual Object Retrieval
Zhu, C.-Z., Jeǵou, H., & Satoh, S. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.214 · Cited by 41
Self-citationTowards semantic embedding in visual vocabulary
Ji, R., Yao, H., Sun, X., et al. (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.2010.5540118 · Cited by 43
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Gehrig, M., Stumm, E. S., Hinzmann, T., & Siegwart, R. (2017) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2017.7989362 · Cited by 51
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A second model labelled each claim on 2026-10-08 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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