Unsupervised graph reasoning distillation hashing for multimodal hamming space search with vision-language model-Reference-Cited by-同舟云学术

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Unsupervised graph reasoning distillation hashing for multimodal hamming space search with vision-language model

Published:2024-03-30 Issue:2 Volume:13 Page:
ISSN:2192-6611
Container-title:International Journal of Multimedia Information Retrieval
language:en
Short-container-title:Int J Multimed Info Retr

Author:

Sun Lina,Dong Yumin

Funder

Postgraduate Scientific Research Innovation Project of Chongqing Normal University

Open Fund of Advanced Cryptography and System Security Key Laboratory of Sichuan Province

National Natural Science Foundation of China

Science and Technology Research Program of Chongqing Municipal Education Commission

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s13735-024-00326-8.pdf

Reference52 articles.

1. Luo X, Wang H, Wu D, Chen C, Deng M, Huang J, Hua X-S (2023) A survey on deep hashing methods. ACM Trans Knowl Discov Data 17(1):1–50

2. Zhu L, Zheng C, Guan W, Li J, Yang Y, Shen HT (2023) Multi-modal hashing for efficient multimedia retrieval: a survey. IEEE Trans Knowl Data Eng

3. Li L, Zheng B, Sun W (2022) Adaptive structural similarity preserving for unsupervised cross modal hashing. In: Proceedings of the 30th ACM international conference on multimedia, pp 3712–3721

4. Singh A, Gupta S (2022) Learning to hash: a comprehensive survey of deep learning-based hashing methods. Knowl Inf Syst 64(10):2565–2597

5. Su S, Zhong Z, Zhang C (2019) Deep joint-semantics reconstructing hashing for large-scale unsupervised cross-modal retrieval. In: Proceedings of the IEEE/CVF international conference on computer vision, pp 3027–3035

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