VideoCLIP 2.0: An Interactive CLIP-Based Video Retrieval System for Novice Users at VBS2024
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-53302-0_37
Reference14 articles.
1. Amato, G., et al.: VISIONE at video browser showdown 2023. In: Dang-Nguyen, D.T., et al. (eds.) MultiMedia Modeling, MMM 2023. LNCS, vol. 13833, pp. 615–621. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-27077-2_48
2. Berns, F., Rossetto, L., Schoeffmann, K., Beecks, C., Awad, G.: V3C1 dataset: an evaluation of content characteristics. In: Proceedings of the 2019 on International Conference on Multimedia Retrieval, ICMR 2019, pp. 334–338, New York, NY, USA. Association for Computing Machinery (2019)
3. Hezel, N., Schall, K., Jung, K., Barthel, K.U.: Efficient search and browsing of large-scale video collections with vibro. In: Þór Jónsson, B., et al. (eds.) MMM 2022. LNCS, vol. 13142, pp. 487–492. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-98355-0_43
4. Lokoč, J., et al.: Interactive video retrieval in the age of effective joint embedding deep models: lessons from the 11th VBS. Multimedia Syst. 29(6), 3481–3504 (2023)
5. Lokoč, J., et al.: Is the reign of interactive search eternal? Findings from the video browser showdown 2020. ACM Trans. Multimedia Comput. Commun. Appl. 17(3), 1–26 (2021)
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