The 2023 video similarity dataset and challenge
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Published:2024-06
Issue:
Volume:243
Page:103997
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ISSN:1077-3142
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Container-title:Computer Vision and Image Understanding
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language:en
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Short-container-title:Computer Vision and Image Understanding
Author:
Pizzi Ed, Kordopatis-Zilos GiorgosORCID, Patel Hiral, Postelnicu Gheorghe, Nagavara Ravindra Sugosh, Gupta Akshay, Papadopoulos SymeonORCID, Tolias Giorgos, Douze Matthijs
Funder
Czech Science Foundation Horizon 2020
Reference55 articles.
1. Google Landmark Recognition Challenge;Araujo,2018 2. Content-based video copy detection benchmarking at TRECVID;Awad;ACM Trans. Inf. Syst.,2014 3. Baraldi, L., Douze, M., Cucchiara, R., Jégou, H., 2018. LAMV: Learning to Align and Match Videos with Kernelized Temporal Layers. In: Proc. CVPR. 4. Black, A., Jenni, S., Bui, T., Tanjim, M.M., Petrangeli, S., Sinha, R., Swaminathan, V., Collomosse, J., 2023. VADER: Video Alignment Differencing and Retrieval. In: Proc. ICCV. 5. Cai, Y., Yang, L., Ping, W., Wang, F., Mei, T., Hua, X.S., Li, S., 2011. Million-scale near-duplicate video retrieval system. In: Proc. ACM MM.
Cited by
1 articles.
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