The DOI matches its Crossref record; 38 of the 40 references it cites were found in a registry or an index.
Deep hashing for compact binary codes learning
Abstract
In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for large scale visual search. Unlike most existing binary codes learning methods which seek a single linear projection to map each sample into a binary vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the nonlinear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the deep network: 1) the loss between the original real-valued feature descriptor and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) by including one discriminative term into the objective function of DH which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes. Experimental results show the superiority of the proposed approach over the state-of-the-arts.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Learning Multiple Layers of Features from Tiny Images
Krizhevsky, A. (2024) · doi:10.57702/zp44cu3g · Cited by 23,889
Reducing the dimensionality of data with neural networks
Hinton, G. E., & Salakhutdinov, R. R. (2006) · Science · doi:10.1126/science.1127647 · Cited by 20,928
Learning Deep Architectures for AI
Bengio, Y. (2009) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000006 · Cited by 7,330
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
Taigman, Y., Yang, M., Ranzato, M., & Wolf, L. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.220 · Cited by 6,542
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
Oliva, A., & Torralba, A. B. (2001) · International Journal of Computer Vision · doi:10.1023/a:1011139631724 · Cited by 6,321
3D Convolutional Neural Networks for Human Action Recognition
Ji, S., Xu, W., Yang, M., & Yu, K. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.59 · Cited by 6,313
Learning Deep Architectures for AI
Bengio, Y. (2009) · now publishers, Inc. eBooks · doi:10.1561/9781601982957 · Cited by 5,050
Datta, R., Joshi, D., Li, J., & Wang, J. Z. (2008) · ACM Computing Surveys · doi:10.1145/1348246.1348248 · Cited by 3,080
Lee, H., Grosse, R., Ranganath, R., & Ng, A. Y. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning · doi:10.1145/1553374.1553453 · Cited by 2,412
Research works printed but not linked: 1
- taylor, 2010, Convolutionallearning of spatio-temporal features, ECCV, 140
Cited by
Sorted by citations
Deep Hashing Network for Unsupervised Domain Adaptation
Venkateswara, H., Eusebio, J., Chakraborty, S., & Panchanathan, S. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.572 · Cited by 2,171
Wang, J., Zhang, T., Song, J., Sebe, N., & Shen, H. T. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2699960 · Cited by 1,055
Image Matching from Handcrafted to Deep Features: A Survey
Ma, J.-Y., Jiang, X., Fan, A., Jiang, J., & Yan, J. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-020-01359-2 · Cited by 977
Person Re-identification: Past, Present and FuturePreprint
Zheng, L., Yang, Y., & Hauptmann, A. G. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1610.02984 · Cited by 1,240
Deep Supervised Hashing for Fast Image Retrieval
Liu, H., Wang, R., Shan, S., & Chen, X. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.227 · Cited by 933
Jiang, Q.-Y., & Li, W.-J. (2017) · 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.2017.348 · Cited by 913
HashNet: Deep Learning to Hash by Continuation
Cao, Z., Long, M., Wang, J., & Yu, P. S. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.598 · Cited by 777
Deep Hashing Network for Efficient Similarity Retrieval
Zhu, H., Long, M., Wang, J., & Cao, Y. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i1.10235 · Cited by 664
Feature Learning based Deep Supervised Hashing with Pairwise LabelsPreprint
Li, W.-J., Wang, S., & Kang, W.-C. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.03855 · Cited by 643
Learning to Hash for Indexing Big Data—A Survey
Wang, J., Liu, W., Kumar, S., & Chang, S. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2487976 · Cited by 534
Li, W., Zhang, Y., Sun, Y., Wang, W., Li, M., Zhang, W., & Lin, X. (2019) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2019.2909204 · Cited by 501
Unsupervised Deep Hashing with Similarity-Adaptive and Discrete Optimization
Shen, F., Xu, Y. L., Liu, L., Yang, Y., Huang, Z. H., & Shen, H. T. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2789887 · Cited by 405
Deep Cauchy Hashing for Hamming Space Retrieval
Cao, Y., Long, M., Liu, B., & Wang, J. (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.2018.00134 · Cited by 389
Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks
Lin, K., Lu, J., Chen, C., & Zhou, J. (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.2016.133 · Cited by 368
Self-citationLearning Discrete Representations via Information Maximizing Self-Augmented TrainingPreprint
Hu, W., Miyato, T., Tokui, S., Matsumoto, E., & Sugiyama, M. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1702.08720 · Cited by 372
A Decade Survey of Content Based Image Retrieval Using Deep Learning
Dubey, S. R. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3080920 · Cited by 390
Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks
Yang, H., Lin, K., & Chen, C. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2666812 · Cited by 340
Deep Sketch Hashing: Fast Free-Hand Sketch-Based Image Retrieval
Liu, L., Shen, F., Shen, Y., Liu, X., & Shao, L. (2017) · 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.2017.247 · Cited by 292
Self-Supervised Video Hashing With Hierarchical Binary Auto-Encoder
Song, J., Zhang, H., Li, X., Gao, L., Wang, M., & Hong, R. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2814344 · Cited by 283
Fast Supervised Discrete Hashing
Gui, J., Liu, T., Sun, Z., Tao, D., & Tan, T. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2678475 · Cited by 272
Supervised Hash Coding With Deep Neural Network for Environment Perception of Intelligent Vehicles
Yan, C. C., Xie, H., Yang, D., Yin, J. P., Zhang, Y., & Dai, Q. (2017) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2017.2749965 · Cited by 248
A Survey on Deep Hashing Methods
Luo, X., Wang, H., Wu, D., Chen, C., Deng, M., Huang, J., & Hua, X.-S. (2023) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3532624 · Cited by 241
Duan, J., Bello, G., Schlemper, J., Bai, W., Dawes, T. J. W., Biffi, C., de Marvao, A., Doumoud, G., O'Regan, D. P., & Rueckert, D. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2894322 · Cited by 227
Deep Quantization Network for Efficient Image Retrieval
Cao, Y., Long, M., Wang, J., Zhu, H., & Wen, Q. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i1.10455 · Cited by 224
Deep Supervised Hashing with Triplet Labels
Wang, X., Shi, Y., & Kitani, K. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-54181-5_5 · Cited by 220
Binary Generative Adversarial Networks for Image Retrieval
Song, J., He, T., Gao, L., Xu, X., Hanjalić, A., & Shen, H. T. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11276 · Cited by 204
Weakly-supervised Semantic Guided Hashing for Social Image Retrieval
Li, Z., Tang, J., Zhang, L., & Yang, J. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-020-01331-0 · Cited by 192
Learning to Hash with Binary Deep Neural Network
Do, T.-T., Doan, A.-D., & Cheung, N. M. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46454-1_14 · Cited by 181
Graph PCA Hashing for Similarity Search
Zhu, X., Li, X., Zhang, S., Xu, Z., Yu, L., & Wang, C. (2017) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2017.2703636 · Cited by 190
Quantization-based hashing: a general framework for scalable image and video retrieval
Song, J., Gao, L., Liu, L., Zhu, X., & Sebe, N. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.03.021 · Cited by 183
Aggregation-Based Graph Convolutional Hashing for Unsupervised Cross-Modal Retrieval
Zhang, P.-F., Li, Y., Huang, Z. H., & Xu, X.-S. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3053766 · Cited by 188
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs
Yang, E., Liu, T., Deng, C. D., Liu, W., & Tao, D. (2019) · 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.2019.00306 · Cited by 170
Unsupervised Semantic-Preserving Adversarial Hashing for Image Search
Deng, C. D., Yang, E., Liu, T., Li, J., Liu, W., & Tao, D. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2903661 · Cited by 169
Zero-Shot Sketch-Image Hashing
Shen, Y., Liu, L., Shen, F., & Shao, L. (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.2018.00379 · Cited by 168
A Fast Optimization Method for General Binary Code Learning
Shen, F., Zhou, X. S., Yang, Y., Song, J., Shen, H. T., & Tao, D. (2016) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2612883 · Cited by 157
Exploring Auxiliary Context: Discrete Semantic Transfer Hashing for Scalable Image Retrieval
Zhu, L., Huang, Z. H., Li, Z., Xie, L., & Shen, H. T. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2797248 · Cited by 158
Deep Metric Learning for Visual Understanding: An Overview of Recent Advances
Lu, J., Hu, J., & Zhou, J. (2017) · IEEE Signal Processing Magazine · doi:10.1109/msp.2017.2732900 · Cited by 160
Self-citationLearning to Break Deep Perceptual Hashing: The Use Case NeuralHash
Struppek, L., Hintersdorf, D., Neider, D., & Kersting, K. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3531146.3533073 · Cited by 153
Unsupervised Deep Video Hashing via Balanced Code for Large-Scale Video Retrieval
Wu, G., Han, J., Guo, Y., Liu, L., Ding, G., Ni, Q., & Shao, L. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2882155 · Cited by 148
Latent Semantic Minimal Hashing for Image Retrieval
Lu, X., Zheng, X., & Li, X. (2016) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2627801 · Cited by 148
Deep Visual-Semantic Quantization for Efficient Image Retrieval
Cao, Y., Long, M., Wang, J., & Liu, S. (2017) · 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.2017.104 · Cited by 149
Accelerating Large-Scale Inference with Anisotropic Vector QuantizationPreprint
Guo, R., Sun, P., Lindgren, E., Geng, Q., Simcha, D., Chern, F., & Kumar, S. (2019) · arXiv (Cornell University) · doi:10.4230/lipics.esa.2022.54 · Cited by 146
Graph Convolutional Network Hashing
Zhou, X. S., Shen, F., Liu, L., Liu, W., Nie, L., Yang, Y., & Shen, H. T. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2883970 · Cited by 145
Auto-Encoding Twin-Bottleneck Hashing
Shen, Y., Qin, J., Chen, J., Yu, M., Liu, L., Zhu, F., Shen, F., & Shao, L. (2020) · 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/cvpr42600.2020.00289 · Cited by 142
SCRATCH: A Scalable Discrete Matrix Factorization Hashing Framework for Cross-Modal Retrieval
Chen, Z.-D., Li, C.-X., Luo, X., Nie, L., Zhang, W., & Xu, X.-S. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2911359 · Cited by 129
Deep Asymmetric Pairwise Hashing
Shen, F., Gao, X., Liu, L., Yang, Y., & Shen, H. T. (2017) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3123266.3123345 · Cited by 124
Fast Training of Triplet-Based Deep Binary Embedding Networks
Zhuang, B., Lin, G., Shen, C., & Reid, I. D. (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.2016.641 · Cited by 125
Asymmetric Binary Coding for Image Search
Shen, F., Yang, Y., Liu, L., Liu, W., Tao, D., & Shen, H. T. (2017) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2017.2699863 · Cited by 120
Unsupervised Deep Generative Adversarial Hashing Network
Dizaji, K. G., Zheng, F., Nourabadi, N. S., Yang, Y., Deng, C. D., & Huang, 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.2018.00386 · Cited by 122
Deep Hash Learning for Remote Sensing Image Retrieval
Liu, C., Ma, J., Tang, X., Liu, F., Zhang, X., & Jiao, L. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3007533 · Cited by 125
Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features
Lu, X., Chen, Y., & Li, X. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2755766 · Cited by 119
HashGAN: Deep Learning to Hash with Pair Conditional Wasserstein GAN
Cao, Y., Liu, B., Long, M., & Wang, J. (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.2018.00140 · Cited by 120
Deep Semantic Multimodal Hashing Network for Scalable Image-Text and Video-Text Retrievals
Jin, L., Li, Z., & Tang, J. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.2997020 · Cited by 128
Deep Discrete Supervised Hashing
Jiang, Q.-Y., Cui, X., & Li, W.-J. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2864894 · Cited by 118
Adversarial Examples for Hamming Space Search
Yang, E., Liu, T., Deng, C. D., & Tao, D. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2882908 · Cited by 121
Yang, F., Kale, A., Bubnov, Y., Stein, L., Wang, Q., Kiapour, H., & Piramuthu, R. (2017) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3097983.3098162 · Cited by 123
Liong, V. E., Lu, J., Tan, Y., & Zhou, J. (2016) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2016.2645404 · Cited by 115
Self-citationLiu, B., Cao, Y., Long, M., Wang, J., & Wang, J. (2018) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3240508.3240516 · Cited by 108
Learning to Hash With Optimized Anchor Embedding for Scalable Retrieval
Guo, Y., Ding, G., Liu, L., Han, J., & Shao, L. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2652730 · Cited by 108
Efficient Training of Very Deep Neural Networks for Supervised Hashing
Zhang, Z., Chen, Y., & Saligrama, V. (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.2016.165 · Cited by 109
Balanced Self-Paced Learning for Generative Adversarial Clustering Network
Dizaji, K. G., Wang, X., Deng, C. D., & Huang, H. (2019) · 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.2019.00452 · Cited by 108
Unsupervised Learning of Discriminative Attributes and Visual Representations
Huang, C., Loy, C. C., & Tang, X. (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.2016.559 · Cited by 102
Deep Unsupervised Image Hashing by Maximizing Bit Entropy
Li, Y., & van Gemert, J. C. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i3.16296 · Cited by 107
Hashing with Mutual Information
Çakir, F., He, K., Bargal, S. A., & Sclaroff, S. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2914897 · Cited by 99
Differentiable Cross-modal Hashing via Multimodal Transformers
Tu, J., Liu, X., Lin, Z., Hong, R., & Wang, M. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548187 · Cited by 104
Deep Ordinal Hashing With Spatial Attention
Jin, L., Shu, X., Li, K., Li, Z., Qi, G.-J., & Tang, J. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2883522 · Cited by 94
One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning ObjectivePreprint
Hoe, J. T., Ng, K. W., Zhang, T., Chan, C. S., Song, Y.-Z., & Xiang, T. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.14449 · Cited by 98
Supervised Discrete Hashing With Relaxation
Gui, J., Liu, T., Sun, Z., Tao, D., & Tan, T. (2016) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2016.2636870 · Cited by 95
Generative Domain-Migration Hashing for Sketch-to-Image Retrieval
Zhang, J., Shen, F., Liu, L., Zhu, F., Yu, M., Shao, L., Shen, H. T., & Gool, L. V. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01216-8_19 · Cited by 95
Fast Scalable Supervised Hashing
Luo, X., Nie, L., He, X., Wu, Y. L., Chen, Z.-D., & Xu, X.-S. (2018) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3209978.3210035 · Cited by 91
Unsupervised Deep Hashing With Pseudo Labels for Scalable Image Retrieval
Zhang, H., Liu, L., Long, Y., & Shao, L. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2781422 · Cited by 92
Zhang, H., Wang, M., Hong, R., & Chua, T. (2016) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2964284.2964308 · Cited by 91
Supervised deep hashing for scalable face image retrieval
Tang, J., Li, Z., & Zhu, X. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.03.028 · Cited by 91
Deep Semantic Hashing with Generative Adversarial Networks
Qiu, Z., Pan, Y., Yao, T., & Mei, T. (2017) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3077136.3080842 · Cited by 91
Binary Hashing for Approximate Nearest Neighbor Search on Big Data: A Survey
Cao, Y., Qi, H., Zhou, W., Kato, J., Li, K., Liu, X., & Gui, J. (2017) · IEEE Access · doi:10.1109/access.2017.2781360 · Cited by 93
Sitcom-star-based clothing retrieval for video advertising: a deep learning framework
Zhang, H., Ji, Y., Huang, W., & Liu, L. (2018) · Neural Computing and Applications · doi:10.1007/s00521-018-3579-x · Cited by 89
Adaptive hash retrieval with kernel based similarity
Bai, X. P., Yan, C., Yang, H., Bai, L., Zhou, J. W., & Hancock, E. R. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.03.020 · Cited by 87
Self-citationDeep balanced discrete hashing for image retrieval
Zheng, X., Zhang, Y., & Lu, X. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.04.037 · Cited by 83
Hierarchical Clustering-Based Graphs for Large Scale Approximate Nearest Neighbor Search
Muñoz, J. A. V., Gonçalves, M. A., Dias, Z., & Torres, R. D. S. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.106970 · Cited by 84
Two-Stream Deep Hashing With Class-Specific Centers for Supervised Image Search
Deng, C. D., Yang, E., Liu, T., & Tao, D. (2019) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2019.2929068 · Cited by 86
Learning binary codes with neural collaborative filtering for efficient recommendation systems
Li, Y., Wang, S., Pan, Q., Peng, H., Yang, T., & Cambria, E. (2019) · Knowledge-Based Systems · doi:10.1016/j.knosys.2019.02.012 · Cited by 81
Learning Deep Binary Descriptor with Multi-quantization
Duan, Y., Lu, J., Wang, Z., Feng, J., & Zhou, J. (2017) · 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.2017.516 · Cited by 80
Self-citationWeakly Supervised Multimodal Hashing for Scalable Social Image Retrieval
Tang, J., & Li, Z. (2017) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2017.2715227 · Cited by 79
Deep Semantic-Preserving Ordinal Hashing for Cross-Modal Similarity Search
Jin, L., Li, K., Li, Z., Xiao, F., Qi, G.-J., & Tang, J. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2869601 · Cited by 77
Deep Hashing Network for Unsupervised Domain Adaptation
Ramakrishnan, R., Nagabandi, B., Eusébio, J., Chakraborty, S., Venkateswara, H., & Panchanathan, S. (2020) · Springer eBooks · doi:10.1007/978-3-030-45529-3_4 · Cited by 101
Distributed Adaptive Binary Quantization for Fast Nearest Neighbor Search
Liu, X., Li, Z., Deng, C. D., & Tao, D. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2729896 · Cited by 76
TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval
Chen, Y., Zhang, S., Liu, F., Chang, Z., Ye, M., & Qi, Z. (2022) · International Conference on Multimedia Retrieval · doi:10.1145/3512527.3531405 · Cited by 87
Variational Deep Semantic Hashing for Text Documents
Chaidaroon, S., & Fang, Y. (2017) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3077136.3080816 · Cited by 76
Unsupervised Deep Learning of Compact Binary Descriptors
Lin, K., Lu, J., Chen, C., Zhou, J., & Sun, M. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2833865 · Cited by 75
Self-citationSupervised Quantization for Similarity Search
Wang, X., Zhang, T., Qi, G.-J., Tang, J., & Wang, J. (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.2016.222 · Cited by 75
Discriminative Deep Quantization Hashing for Face Image Retrieval
Tang, J., Lin, J., Li, Z., & Yang, J. J. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2816743 · Cited by 72
Deep Secure Encoding for Face Template Protection
Pandey, R., Zhou, Y., Kota, B. U., & Govindaraju, V. (2016) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2016.17 · Cited by 74
Learning binary code for fast nearest subspace search
Zhou, L., Bai, X. P., Liu, X., Zhou, J. W., & Hancock, E. R. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.107040 · Cited by 68
Self-citationUnified Binary Generative Adversarial Network for Image Retrieval and Compression
Song, J., He, T., Gao, L., Xu, X., Hanjalić, A., & Shen, H. T. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-020-01305-2 · Cited by 67
Deep face fuzzy vault: Implementation and performance
Rathgeb, C., Merkle, J., Scholz, J., Tams, B., & Nesterowicz, V. (2021) · Computers & Security · doi:10.1016/j.cose.2021.102539 · Cited by 67
Structured deep hashing with convolutional neural networks for fast person re-identification
Wu, L. Y., Wang, Y., Ge, Z., Hu, Q., & Li, X. (2017) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2017.11.009 · Cited by 66
Inductive Structure Consistent Hashing via Flexible Semantic Calibration
Zhang, Z., Liu, L., Luo, Y., Huang, Z. H., Shen, F., Shen, H. T., & Lu, G. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3018790 · Cited by 66
ExchNet: A Unified Hashing Network for Large-Scale Fine-Grained Image Retrieval
Cui, Q., Jiang, Q.-Y., Wei, X.-S., Li, W.-J., & Yoshie, O. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58580-8_12 · Cited by 66
Unsupervised Binary Representation Learning with Deep Variational Networks
Shen, Y., Liu, L., & Shao, L. (2019) · International Journal of Computer Vision · doi:10.1007/s11263-019-01166-4 · Cited by 66
Deep triplet hashing network for case-based medical image retrieval
Fang, J., Fu, H., & Liu, J. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.101981 · Cited by 66
Metadata
- Authors
- Liong, V. E., Lu, J., Wang, G., Moulin, P., & Zhou, J.
- Affiliations
- Advanced Digital Sciences Center (SG)
- Nanyang Technological University (SG)
- University of Illinois Urbana-Champaign (US)
- Tsinghua University (CN)
- Venue
- 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2015-06
- Pages
- 2475-2483
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W1956333070
- Cited by
- 545
- References
- 40
- Citations by year
- 2026: 2 · 2025: 17 · 2024: 19 · 2023: 28 · 2022: 46 · 2021: 49 · 2020: 70 · 2019: 82 · 2018: 88 · 2017: 102 · 2016: 33 · 2015: 9
- FWCI
- 31.71
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
- 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 › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- deep hashing, binary code learning, compact binary codes, visual search, large-scale 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.
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 ›
Are you an author, or do you see a problem with this page? Request a review
