The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
Prompting Visual-Language Models for Efficient Video Understanding
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Language Models are Few-Shot Learners
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · arXiv · doi:10.48550/arxiv.2005.14165 · Cited by 23,372
Advances in neural information processing systems 7
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Learning Transferable Visual Models From Natural Language Supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al. (2021) · arXiv · doi:10.48550/arxiv.2103.00020 · Cited by 15,293
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Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
Carreira, J., & Zisserman, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.502 · Cited by 9,570
SlowFast Networks for Video Recognition
Feichtenhofer, C., Fan, H., Malik, J., & He, K. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00630 · Cited by 4,007
Hmdb: a large video database for human motion recognition
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A Closer Look at Spatiotemporal Convolutions for Action Recognition
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The Power of Scale for Parameter-Efficient Prompt Tuning
Lester, B., Al-Rfou, R., & Constant, N. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2021.emnlp-main.243 · Cited by 3,096
Cited by
Jia, M., Tang, L., Chen, B.-C., Cardie, C., Belongie, S., Hariharan, B., & Lim, S.-N. (2022) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-19827-4_41 · Cited by 1,965
A systematic survey of prompt engineering on vision-language foundation models
Gu, J., Han, Z., Chen, S., Beirami, A., He, B., Zhang, G., Liao, R., Qin, Y., Tresp, V., & Torr, P. (2023) · arXiv · doi:10.48550/arxiv.2307.12980 · Cited by 280
Frozen CLIP Models are Efficient Video Learners
Lin, Z., Geng, S., Zhang, R., Gao, P., de Melo, G., Wang, X., Dai, J., Qiao, Y., & Li, H. (2022) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-19833-5_23 · Cited by 213
Vision-Language Pre-Training: Basics, Recent Advances, and Future Trends
Gan, Z., Li, L., Li, C., Wang, L., Liu, Z., & Gao, J. (2022) · Foundations and Trends® in Computer Graphics and Vision · doi:10.1561/0600000105 · Cited by 155
Visual cognition in multimodal large language models
Schulze Buschoff, L. M., Akata, E., Bethge, M., & Schulz, E. (2025) · Nature Machine Intelligence · doi:10.1038/s42256-024-00963-y · Cited by 83
Metadata
- Authors
- Ju, C., Han, T., Zheng, K., Zhang, Y., & Xie, W.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Nature Switzerland
- Published
- 2022
- Pages
- 105-124
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W4312480274
- Cited by
- 391
- References
- 75
- FWCI
- 32.26
- Type
- conference paper
- Language
- en
- Open access
- green
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