Optimizing the Interactive Video Retrieval Tool Vibro for the Video Browser Showdown 2024
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-53302-0_33
Reference18 articles.
1. 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 (2019)
2. Dosovitskiy, A., et al.: An image is worth 16 $$\times $$ 16 words: transformers for image recognition at scale. CoRR (2020)
3. Fang, Y., et al.: EVA: exploring the limits of masked visual representation learning at scale (2022). https://doi.org/10.48550/ARXIV.2211.07636. https://arxiv.org/abs/2211.07636
4. Heller, S., et al.: Interactive video retrieval evaluation at a distance: comparing sixteen interactive video search systems in a remote setting at the 10th video browser showdown. Int. J. Multim. Inf. Retr. 11(1), 1–18 (2022). https://doi.org/10.1007/s13735-021-00225-2
5. Hendrycks, D., Zhao, K., Basart, S., Steinhardt, J., Song, D.: Natural adversarial examples (2019). https://doi.org/10.48550/ARXIV.1907.07174. https://arxiv.org/abs/1907.07174
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