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DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval. (arXiv:2106.13266v2 [cs.CV] UPDATED)
July 14, 2022, 1:12 a.m. | Giorgos Kordopatis-Zilos, Christos Tzelepis, Symeon Papadopoulos, Ioannis Kompatsiaris, Ioannis Patras
cs.CV updates on arXiv.org arxiv.org
In this paper, we address the problem of high performance and computationally
efficient content-based video retrieval in large-scale datasets. Current
methods typically propose either: (i) fine-grained approaches employing
spatio-temporal representations and similarity calculations, achieving high
performance at a high computational cost or (ii) coarse-grained approaches
representing/indexing videos as global vectors, where the spatio-temporal
structure is lost, providing low performance but also having low computational
cost. In this work, we propose a Knowledge Distillation framework, called
Distill-and-Select (DnS), that starting from …
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