Application of CLIP for efficient zero-shot learning-Reference-Cited by-同舟云学术

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Application of CLIP for efficient zero-shot learning

Published:2024-07-26 Issue:4 Volume:30 Page:
ISSN:0942-4962
Container-title:Multimedia Systems
language:en
Short-container-title:Multimedia Systems

Author:

Yang Hairui,Wang Ning,Li Haojie,Wang Lei,Wang Zhihui

Funder

National Natural Science Foundation of China, China

The Taishan Scholar Program of Shandong Province

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00530-024-01414-9.pdf

Reference56 articles.

1. Lampert, C.H., Nickisch, H., Harmeling, S.: Learning to detect unseen object classes by between-class attribute transfer. In: CVPR, pp. 951–958 (2009). https://doi.org/10.1109/CVPR.2009.5206594

2. Wang, N., Liu, B., Niu, M., Meng, K., Li, H., Liu, B., Wang, Z.: Semantic place prediction with user attribute in social media. IEEE Multim. 28(4), 29–37 (2021). https://doi.org/10.1109/MMUL.2021.3089719

3. Fu, Y., Hospedales, T.M., Xiang, T., Gong, S.: Transductive multi-view zero-shot learning. IEEE Trans. Pattern Anal. Mach. Intell. 37(11), 2332–2345 (2015). https://doi.org/10.1109/TPAMI.2015.2408354

4. Kodirov, E., Xiang, T., Gong, S.: Semantic autoencoder for zero-shot learning. In: CVPR, pp. 4447–4456 (2017). https://doi.org/10.1109/CVPR.2017.473

5. Zhang, L., Xiang, T., Gong, S.: Learning a deep embedding model for zero-shot learning. In: CVPR, pp. 3010–3019 (2017). https://doi.org/10.1109/CVPR.2017.321

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