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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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Cheng, W., Lin, W., Chen, K., & Zhang, X. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00112 · Cited by 29
Attention-Based Query Expansion Learning
Gordo, A., Radenović, F., & Berg, T. L. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58604-1_11 · Cited by 41
Polar Embedding for Aurora Image Retrieval
Yang, X., Gao, X., & Tian, Q. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2442913 · Cited by 30
Fast content-based image retrieval using convolutional neural network and hash function
Varga, D., & Szirányi, T. (2016) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2016.7844637 · Cited by 31
In-video product annotation with web information mining
Li, G., Wang, M., Lu, Z., et al. (2012) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/2379790.2379797 · Cited by 30
Embedding spatial context information into inverted filefor large-scale image retrieval
Liu, Z., Li, H., Zhou, W., et al. (2012) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2393347.2393380 · Cited by 30
Improved Hamming Distance Search Using Variable Length Hashing
Ong, E.-J., & Bober, M. Z. (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.2016.220 · Cited by 30
Deep Region Hashing for Generic Instance Search from Images
Song, J., He, T., Gao, L., Xu, X., & Shen, H. T. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11277 · Cited by 30
Heo, J., Lin, Z., & Yoon, S. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2853161 · Cited by 29
An Interpolative AMBTC-based high-payload RDH scheme for encrypted images
Shiu, P.-F., Tai, W., Jan, J., et al. (2019) · Signal Processing Image Communication · doi:10.1016/j.image.2019.01.003 · Cited by 30
Yu, P., Tang, J., Xia, Z., et al. (2023) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2022.3233421 · Cited by 30
Optimized residual vector quantization for efficient approximate nearest neighbor search
Ai, L., Yu, J., Wu, Z., He, Y., & Guan, T. (2015) · Multimedia Systems · doi:10.1007/s00530-015-0470-9 · Cited by 29
SIFT Meets CNN: A Decade Survey of Instance RetrievalPreprint
Zheng, L., Yang, Y. P., & Tian, Q. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1608.01807 · Cited by 30
MSIDX: Multi-Sort Indexing for Efficient Content-Based Image Search and Retrieval
Tiakas, E., Rafailidis, D., Dimou, A., & Daras, P. (2013) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2013.2247989 · Cited by 29
Binary Set Embedding for Cross-Modal Retrieval
Yu, M., Liu, L., & Shao, L. (2016) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2609463 · Cited by 29
End‐to‐End Optimization of Metalens for Broadband and Wide‐Angle Imaging
Park, Y., Kim, Y., Kim, C., Lee, G., Choi, H., Choi, T., Jeong, Y., & Lee, B. (2025) · Advanced Optical Materials · doi:10.1002/adom.202402853 · Cited by 28
Image Retrieval with Reciprocal and Shared Nearest Neighbors
Delvinioti, A., Jeǵou, H., Amsaleg, L., et al. (2014) · International Conference on Computer Vision Theory and Applications · doi:10.5220/0004672303210328 · Cited by 28
Self-citationWeakly supervised sparse coding with geometric consistency pooling
Cao, L., Ji, R., Gao, Y., Yang, Y., & Tian, Q. (2012) · 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.2012.6248102 · Cited by 28
Adding Affine Invariant Geometric Constraint for Partial-Duplicate Image Retrieval
Wu, Z., Xu, Q., Jiang, S., Huang, Q., Cui, P., & Li, L. (2010) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2010.212 · Cited by 28
Distances and weighting schemes for bag of visual words image retrieval
Tirilly, P., Claveau, V., & Gros, P. (2010) · Multimedia Information Retrieval · doi:10.1145/1743384.1743438 · Cited by 28
Deep binary codes for large scale image retrieval
Wu, S., Oerlemans, A., Bakker, E. M., & Lew, M. S. (2017) · Neurocomputing · doi:10.1016/j.neucom.2016.12.070 · Cited by 27
Toward Knowledge as a Service Over Networks: A Deep Learning Model Communication Paradigm
Chen, Z., Duan, L., Wang, S., Lou, Y., Huang, T., Wu, D. O., & Gao, W. (2019) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2019.2904360 · Cited by 27
Learning a robust representation via a deep network on symmetric positive definite manifolds
Gao, Z. F., Wu, Y., Bu, X., Yu, T., Yuan, J., & Jia, Y. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.03.007 · Cited by 34
Zhang, Y., & Kumar, A. (2019) · Proceedings of the VLDB Endowment · doi:10.14778/3372716.3372721 · Cited by 26
Revisiting Self-Similarity: Structural Embedding for Image Retrieval
Lee, S., Lee, S., Seong, H., et al. (2023) · 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/cvpr52729.2023.02242 · Cited by 28
From images to scenes: Compressing an image cluster into a single scene model for place recognition
Johns, E., & Yang, G. (2011) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2011.6126328 · Cited by 28
Automatic Ensemble Diffusion for 3D Shape and Image Retrieval
Bai, S., Zhou, Z., Wang, J., Bai, X., Latecki, L. J., & Tian, Q. C. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2863028 · Cited by 27
Learning query-dependent prefilters for scalable image retrieval
Torresani, L., Szummer, M., & Fitzgibbon, A. W. (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.2009.5206582 · Cited by 28
Indexing of the CNN features for the large scale image search
Liu, R., Wei, S., Zhao, Y., & Yang, Y. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-6210-3 · Cited by 27
Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and RetrievalPreprint
Weyand, T., Araújo, A. D. M., Cao, B., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.01804 · Cited by 28
DeepDOF-SE: affordable deep-learning microscopy platform for slide-free histology
Jin, L., Tang, Y., Coole, J. B., Tan, M. T., Zhao, X., Badaoui, H., Robinson, J. T., Williams, M. D., Vigneswaran, N., Gillenwater, A. M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47065-2 · Cited by 30
Building descriptive and discriminative visual codebook for large-scale image applications
Tian, Q. C., Zhang, S. S., Zhou, W., Ji, R., Ni, B., & Sebe, N. (2010) · Multimedia Tools and Applications · doi:10.1007/s11042-010-0636-6 · Cited by 26
Near-Duplicate Image Retrieval Based on Contextual Descriptor
Yao, J., Yang, B., & Zhu, Q. (2014) · IEEE Signal Processing Letters · doi:10.1109/lsp.2014.2377795 · Cited by 27
Maddern, W., Stewart, A. D., & Newman, P. M. (2014) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2014.6856471 · Cited by 27
Instance search retrospective with focus on TRECVID
Awad, G., Kraaij, W., Over, P. L., & Satoh, S. (2017) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-017-0121-3 · Cited by 25
Aurora image search with contextual CNN feature
Yang, X., Gao, X., Song, B., & Yang, D. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.11.059 · Cited by 26
Chen, K., Fürst, J., Kolb, J., Kim, H., Jin, X., Culler, D., & Katz, R. H. (2018) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3161173 · Cited by 28
BoSR: A CNN-based aurora image retrieval method
Yang, X., Wang, N., Song, B., & Gao, X. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.04.012 · Cited by 26
Learning Deep Local Features with Multiple Dynamic Attentions for Large-Scale Image Retrieval
Wu, H., Wang, M., Zhou, W., et al. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01122 · Cited by 27
A Principled Design of Image Representation: Towards Forensic Tasks
Qi, S., Zhang, Y., Wang, C., Zhou, J., & Cao, X. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3204971 · Cited by 29
Descriptor Learning for Omnidirectional Image Matching
Masci, J., Migliore, D., Bronstein, M. M., & Schmidhuber, J. (2013) · Studies in computational intelligence · doi:10.1007/978-3-642-44907-9_3 · Cited by 26
Location recognition over large time lags
Fernando, B., Tommasi, T., & Tuytelaars, T. (2015) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2015.05.016 · Cited by 24
Two-stage pooling of deep convolutional features for image retrieval
Zhi, T., Duan, L., Wang, Y., & Huang, T. (2016) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2016.7532802 · Cited by 28
Indoor/outdoor image classification using GIST image features and neural network classifiers
Tahir, W., Majeed, A., & Rehman, T. (2015) · doi:10.1109/honet.2015.7395428 · Cited by 27
An image-based near-duplicate video retrieval and localization using improved Edit distance
Liu, H., Zhao, Q., Wang, H., Lv, P. M., & Chen, Y. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-016-4176-6 · Cited by 26
A Context-Aware Locality Measure for Inlier Pool Enrichment in Stepwise Image Registration
Zhang, S., Zhao, W., Hao, X., Yang, Y., & Guan, C. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2961480 · Cited by 27
DeepHash: Getting Regularization, Depth and Fine-Tuning RightPreprint
Lin, J., Morère, O., Chandrasekhar, V., Veillard, A., & Goh, H. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1501.04711 · Cited by 25
Block-based image steganalysis: Algorithm and performance evaluation
Cho, S., Cha, B.-H., Gawecki, M., et al. (2013) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2013.05.007 · Cited by 26
On stability of signature-based similarity measures for content-based image retrieval
Beecks, C., Kirchhoff, S., & Seidl, T. (2013) · Multimedia Tools and Applications · doi:10.1007/s11042-012-1334-3 · Cited by 26
Duplicate Discovery on 2 Billion Internet Images
Wang, X., Zhang, L., & Liu, C. (2013) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2013.71 · Cited by 26
ASPset: An outdoor sports pose video dataset with 3D keypoint annotations
Nibali, A., Millward, J., He, Z., & Morgan, S. (2021) · Image and Vision Computing · doi:10.1016/j.imavis.2021.104196 · Cited by 26
Interpretable Semantic Photo Geolocation
Theiner, J., Müller-Budack, E., & Ewerth, R. (2022) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv51458.2022.00154 · Cited by 30
Wang, Y., Chai, X., Gan, Z., et al. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03597-y · Cited by 26
Robust image hashing for content identification through contrastive self-supervised learning
Fonseca-Bustos, J., Ramírez-Gutiérrez, K. A., & Feregrino-Uribe, C. (2022) · Neural Networks · doi:10.1016/j.neunet.2022.09.028 · Cited by 26
Learning to Reduce Scale Differences for Large-Scale Invariant Image Matching
Fu, Y., Zhang, P., Liu, B., Zheng, R. Y., & Wu, Y. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3210602 · Cited by 29
A Comprehensive Survey on Methods for Image Integrity
Capasso, P., Cattaneo, G., & Marsico, M. D. (2023) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3633203 · Cited by 32
Scalable mining of small visual objects
Letessier, P., Buisson, O., & Joly, A. (2012) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2393347.2393431 · Cited by 26
Yue, H., Sun, X., Wu, F., et al. (2012) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2012.52 · Cited by 26
Block-based image steganalysis: Algorithm and performance evaluation
Cho, S., Cha, B.-H., Wang, J., et al. (2010) · doi:10.1109/iscas.2010.5537499 · Cited by 26
Scaling object recognition: Benchmark of current state of the art techniques
Aly, M., Welinder, P., Munich, M. E., et al. (2009) · doi:10.1109/iccvw.2009.5457542 · Cited by 26
Logo detection based on spatial-spectral saliency and partial spatial context
Gao, K., Lin, S., Zhang, Y., et al. (2009) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2009.5202500 · Cited by 26
Multi-trend binary code descriptor: a novel local texture feature descriptor for image retrieval
Yu, L., Feng, L., Wang, H., et al. (2017) · Signal Image and Video Processing · doi:10.1007/s11760-017-1152-1 · Cited by 26
Accurate Smartphone Indoor Visual Positioning Based on a High-Precision 3D Photorealistic Map
Wu, T., Liu, J., Zheng, L., Liu, K., & xu, B. (2018) · Sensors · doi:10.3390/s18061974 · Cited by 24
SSIR: Secure similarity image retrieval in IoT
Yan, H., Chen, Z., & Jia, C. (2018) · Information Sciences · doi:10.1016/j.ins.2018.11.046 · Cited by 26
CDbin: Compact Discriminative Binary Descriptor Learned With Efficient Neural Network
Ye, J., Zhang, S. S., Huang, T., & Rui, Y. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2896095 · Cited by 26
Privacy-preserving content-based image retrieval for mobile computing
Wang, Y., Liu, F., Pang, Z., et al. (2019) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2019.102399 · Cited by 26
Attention-Aware Generalized Mean Pooling for Image RetrievalPreprint
Gu, Y., Li, C., & Xie, J. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.00202 · Cited by 26
Douze, M., & Jeǵou, H. (2014) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2647868.2654892 · Cited by 25
Self-citationRandomized Spatial Context for Object Search
Jiang, Y., Meng, J., Yuan, J., et al. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2405337 · Cited by 25
Landmark Summarization With Diverse Viewpoints
Qian, X., Xue, Y., Yang, X., et al. (2014) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2014.2369731 · Cited by 25
Ge, T., He, K., & Sun, J. Z. (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.2014.125 · Cited by 24
Multiple parenting identification in image phylogeny
Oliveira, A., Ferrara, P., Rosa, A. D., et al. (2014) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2014.7026082 · Cited by 25
Ahmad, J., Sajjad, M., Rho, S., & Baik, S. W. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-016-3436-9 · Cited by 25
Lux, M., Riegler, M. A., Halvorsen, P., et al. (2016) · doi:10.1145/2910017.2910630 · Cited by 25
Image spam classification based on convolutional neural network
Shang, E.-X., & Zhang, H. (2016) · International Conference on Machine Learning and Cybernetics · doi:10.1109/icmlc.2016.7860934 · Cited by 25
A Generic Inverted Index Framework for Similarity Search on the GPU
Zhou, J., Guo, Q., Jagadish, H. V., Krčál, L., Liu, S., Luan, W., Tung, A. K. H., Yang, Y., & Zheng, Y. (2018) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde.2018.00085 · Cited by 24
Large-Scale Image Retrieval with Elasticsearch
Amato, G. M., Bolettieri, P., Carrara, F., et al. (2018) · doi:10.1145/3209978.3210089 · Cited by 25
Low-Overhead Adaptive Brightness Scaling for Energy Reduction in OLED Displays
Pagliari, D. J., Cataldo, S. D., Patti, E., et al. (2019) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2019.2908257 · Cited by 25
Detection of loop closure in SLAM: A DeconvNet based approach
Mukherjee, A., Chakraborty, S., & Saha, S. K. (2019) · Applied Soft Computing · doi:10.1016/j.asoc.2019.04.041 · Cited by 25
A novel feature representation: Aggregating convolution kernels for image retrieval
Wang, Q., Lai, J., Claesen, L., Yang, Z., Lei, L., & Liu, W. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.06.010 · Cited by 25
A BFS-Tree of ranking references for unsupervised manifold learning
Pedronette, D. C. G., Valem, L. P., & Torres, R. D. S. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107666 · Cited by 27
A Local Bag-of-Features Model for Large-Scale Object Retrieval
Lin, Z., & Brandt, J. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15567-3_22 · Cited by 26
Radenović, F., Jeǵou, H., & Chum, O. (2015) · International Conference on Multimedia Retrieval · doi:10.1145/2671188.2749366 · Cited by 25
Self-citationHigh-dimensional indexing technologies for large scale content-based image retrieval: a review
Ai, L., Yu, J., He, Y., & Guan, T. (2013) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/jzus.cide1304 · Cited by 25
Making Residual Vector Distribution Uniform for Distinctive Image Representation
Liu, Z., Li, H., Zhou, W., et al. (2015) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2015.2409693 · Cited by 25
What You See is What You Get? Automatic Image Verification for Online News Content
Elkasrawi, S., Dengel, A., Abdelsamad, A., et al. (2016) · doi:10.1109/das.2016.75 · Cited by 25
One-Shot Fine-Grained Instance Retrieval
Yao, H., Zhang, S. S., Zhang, Y., Li, J., & Tian, Q. (2017) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3123266.3123278 · Cited by 23
Frontiers of Multimedia Research
Chang, S.-F. (2017) · doi:10.1145/3122865 · Cited by 26
Effective Image Retrieval via Multilinear Multi-Index Fusion
Zhang, Z., Xie, Y., Zhang, W., & Tian, Q. (2019) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2019.2915036 · Cited by 25
Zhang, Y., Guan, T., Duan, L., et al. (2014) · Signal Processing · doi:10.1016/j.sigpro.2014.08.029 · Cited by 24
Coding binary local features extracted from video sequences
Baroffio, L., Ascenso, J., Cesana, M., et al. (2014) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2014.7025565 · Cited by 24
An empirical study on the combination of surf features with VLAD vectors for image search
Spyromitros-Xioufis, E., Papadopoulos, S., Kompatsiaris, I. Y., et al. (2012) · International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS) · doi:10.1109/wiamis.2012.6226771 · Cited by 24
Low latency image retrieval with progressive transmission of CHoG descriptors
Chandrasekhar, V., Tsai, S. S., Takacs, G., et al. (2010) · doi:10.1145/1877953.1877966 · Cited by 24
A Novel Local Structure Descriptor for Color Image Retrieval
Zeng, Z. (2016) · Information · doi:10.3390/info7010009 · Cited by 23
Color and texture applied to a signature-based bag of visual words method for image retrieval
dos Santos, J. M., de Moura, E. S., da Silva, A. S., & Torres, R. D. S. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-016-3955-4 · Cited by 23
Will It Last? Learning Stable Features for Long-Term Visual Localization
Dymczyk, M., Stumm, E. S., Nieto, J. I., Siegwart, R., & Gilitschenski, I. (2016) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv.2016.66 · Cited by 21
Enhanced bag of visual words representations for content based image retrieval: a comparative study
Arun, K. S., Govindan, V. K., & Kumar, S. D. M. (2019) · Artificial Intelligence Review · doi:10.1007/s10462-019-09715-6 · Cited by 24
Large Scale Landmark Recognition via Deep Metric Learning
Boiarov, A., & Tyantov, E. (2019) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3357384.3357956 · Cited by 33
Fast Local Spatial Verification for Feature-Agnostic Large-Scale Image Retrieval
Brogan, J., Bharati, A., Moreira, D., Rocha, A. D. R., Bowyer, K. W., Flynn, P. J., & Scheirer, W. J. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3097175 · Cited by 24
Size Matters: Exhaustive Geometric Verification for Image Retrieval Accepted for ECCV 2012
Stewénius, H., Gunderson, S. H., & Pilet, J. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33709-3_48 · Cited by 24
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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