1 |
GONG Y C, LAZEBNIK S, GORDO A, et al. Iterative quantization: a procrustean approach to learning binary codes for large-scale image retrieval[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(12): 2916-2929. 10.1109/tpami.2012.193
|
2 |
RASIWASIA N, COSTA PEREIRA J, COVIELLO E, et al. A new approach to cross-modal multimedia retrieval[C]// Proceedings of the 18th ACM International Conference on Multimedia. New York: ACM, 2010: 251-260. 10.1145/1873951.1873987
|
3 |
冯霞,胡志毅,刘才华. 跨模态检索研究进展综述[J]. 计算机科学, 2021, 48(8): 13-23. 10.11896/jsjkx.200800165
|
|
FENG X, HU Z Y, LIU C H. Survey of research progress on cross-modal retrieval[J]. Computer Science, 2021, 48(8): 13-23. 10.11896/jsjkx.200800165
|
4 |
WANG Y X, CHEN Z D, LUO X, et al. Fast cross-modal hashing with global and local similarity embedding[J]. IEEE Transactions on Cybernetics, 2022, 52(10):10064-10077. 10.1109/tcyb.2021.3059886
|
5 |
梁美玉,王笑笑,杜军平. 基于多模态图和对抗哈希注意力网络的跨媒体细粒度表示学习[J]. 模式识别与人工智能, 2022, 35(3):195-206. 10.16451/j.cnki.issn1003-6059.202203001
|
|
LIANG M Y, WANG X X, DU J P. Cross-media fine-grained representation learning based on multi-modal graph and adversarial hash attention network[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(3):195-206. 10.16451/j.cnki.issn1003-6059.202203001
|
6 |
IRIE G, ARAI H, TANIGUCHI Y. Alternating co-quantization for cross-modal hashing[C]// Proceedings of the 2015 IEEE International Conference on Computer Vision. Piscataway: IEEE, 2015: 1886-1894. 10.1109/iccv.2015.219
|
7 |
ZHANG D Q, LI W J. Large-scale supervised multimodal hashing with semantic correlation maximization[C]// Proceedings of the 28th AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press, 2014: 2177-2183. 10.1609/aaai.v28i1.8995
|
8 |
刘芳名,张鸿. 基于多级语义的判别式跨模态哈希检索算法[J]. 计算机应用, 2021, 41(8): 2187-2192. 10.11772/j.issn.1001-9081.2020101607
|
|
LIU F M, ZHANG H. Cross-modal retrieval algorithm based on multi-level semantic discriminative guided hashing[J]. Journal of Computer Applications, 2021, 41(8): 2187-2192. 10.11772/j.issn.1001-9081.2020101607
|
9 |
YU J, WU X J, KITTLER J. Discriminative supervised hashing for cross-modal similarity search[J]. Image and Vision Computing, 2019, 89: 50-56. 10.1016/j.imavis.2019.06.004
|
10 |
LIU X, HU Z K, LING H B, et al. MTFH: a matrix tri-factorization hashing framework for efficient cross-modal retrieval[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43(3): 964-981. 10.1109/TPAMI.2019.2940446
|
11 |
张成,万源,强浩鹏. 基于知识蒸馏的深度无监督离散跨模态哈希[J]. 计算机应用, 2021, 41(9): 2523-2531. 10.11772/j.issn.1001-9081.2020111785
|
|
ZHANG C, WAN Y, QIANG H P. Deep unsupervised discrete cross-modal hashing based on knowledge distillation[J]. Journal of Computer Applications, 2021, 41(9): 2523-2531. 10.11772/j.issn.1001-9081.2020111785
|
12 |
LIU H, JI R R, WU Y J, et al. Cross-modality binary code learning via fusion similarity hashing[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2017: 6345-6353. 10.1109/cvpr.2017.672
|
13 |
ZHOU J L, DING G G, GUO Y C. Latent semantic sparse hashing for cross-modal similarity search[C]// Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM, 2014: 415-424. 10.1145/2600428.2609610
|
14 |
HU H T, XIE L X, HONG R C, et al. Creating something from nothing: unsupervised knowledge distillation for cross-modal hashing[C]// Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2020: 3120-3129. 10.1109/cvpr42600.2020.00319
|
15 |
GUO J, ZHU W W. Collective affinity learning for partial cross-modal hashing[J]. IEEE Transactions on Image Processing, 2020, 29: 1344-1355. 10.1109/tip.2019.2941858
|
16 |
MANDAL D, CHAUDHURY K N, BISWAS S. Generalized semantic preserving hashing for cross-modal retrieval[J]. IEEE Transactions on Image Processing, 2019, 28(1): 102-112. 10.1109/tip.2018.2863040
|
17 |
LIN Z J, DING G G, HU M Q, et al. Semantics-preserving hashing for cross-view retrieval[C]// Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2015: 3864-3872. 10.1109/cvpr.2015.7299011
|
18 |
TANG J, WANG K, SHAO L. Supervised matrix factorization hashing for cross-modal retrieval[J]. IEEE Transactions on Image Processing, 2016, 25(7): 3157-3166. 10.1109/tip.2016.2564638
|
19 |
LIU X, CHEUNG Y M, HU Z K, et al. Adversarial tri-fusion hashing network for imbalanced cross-modal retrieval[J]. IEEE Transactions on Emerging Topics in Computational Intelligence, 2021, 5(4): 607-619. 10.1109/tetci.2020.3007143
|
20 |
XU X, SHEN F M, YANG Y, et al. Learning discriminative binary codes for large-scale cross-modal retrieval[J]. IEEE Transactions on Image Processing, 2017, 26(5): 2494-2507. 10.1109/tip.2017.2676345
|
21 |
DING G G, GUO Y C, ZHOU J L. Collective matrix factorization hashing for multimodal data[C]// Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2014: 2083-2090. 10.1109/cvpr.2014.267
|
22 |
LIU X B, NIE X S, ZHOU Q, et al. Model optimization boosting framework for linear model hash learning[J]. IEEE Transactions on Image Processing, 2020, 29: 4254-4268. 10.1109/tip.2020.2970577
|
23 |
CAO Y, QI H, ZHOU W R, et al. Binary hashing for approximate nearest neighbor search on big data: a survey[J]. IEEE Access, 2018, 6: 2039-2054. 10.1109/access.2017.2781360
|
24 |
LIN M B, JI R R, LIU H, et al. Supervised online hashing via Hadamard codebook learning[C]// Proceedings of the 26th ACM International Conference on Multimedia. New York: ACM, 2018: 1635-1643. 10.1145/3240508.3240519
|
25 |
YUAN L, WANG T, ZHANG X P, et al. Central similarity quantization for efficient image and video retrieval[C]// Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2020: 3080-3089. 10.1109/cvpr42600.2020.00315
|
26 |
BIAN X M, LAN R S, WANG X Q, et al. Discriminative codebook hashing for supervised video retrieval[J]. Computational Intelligence and Neuroscience, 2021, 2021: No.5845094. 10.1155/2021/5845094
|
27 |
CHEN C, WANG X Q, CHEN X, et al. Discriminative similarity-balanced online hashing for supervised image retrieval[J]. Scientific Programming, 2022, 2022: No.2809222. 10.1155/2022/2809222
|
28 |
LI C X, CHEN Z D, ZHANG P F, et al. SCRATCH: a scalable discrete matrix factorization hashing for cross-modal retrieval[C]// Proceedings of the 26th ACM International Conference on Multimedia. New York: ACM, 2018: 1-9. 10.1145/3240508.3240547
|
29 |
WANG D, WANG Q, HE L H, et al. Joint and individual matrix factorization hashing for large-scale cross-modal retrieval[J]. Pattern Recognition, 2020, 107: No.107479. 10.1016/j.patcog.2020.107479
|
30 |
DATAR M, IMMORLICA N, INDYK P, et al. Locality-sensitive hashing scheme based on p-stable distributions[C]// Proceedings of the 12th Annual Symposium on Computational Geometry. New York: ACM, 2004: 253-262. 10.1145/997817.997857
|
31 |
ZHANG D Q, LI W J. Large-scale supervised multimodal hashing with semantic correlation maximization[C]// Proceedings of the 28th AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press, 2014: 2177-2183. 10.1609/aaai.v28i1.8995
|
32 |
SHEN H T, LIU L C, YANG Y, et al. Exploiting subspace relation in semantic labels for cross-modal hashing[J]. IEEE Transactions on Knowledge and Data Engineering, 2021, 33(10): 3351-3365. 10.1109/tkde.2020.2970050
|