Damen, D.

Doughty, H.

Wray, M.

English

Current video retrieval efforts all found their evaluation on an instance-based assumption, that only a single caption is relevant to a query video and vice versa. We demonstrate that this assumption results in performance comparisons often not indicative of models’ retrieval capabilities. We propose a move to semantic similarity video retrieval, where (i) multiple videos/captions can be deemed equally relevant, and their relative ranking does not affect a method’s reported performance and (ii) retrieved videos/captions are ranked by their similarity to a query. We propose several proxies to estimate semantic similarities in large-scale retrieval datasets, without additional annotations. Our analysis is performed on three commonly used video retrieval datasets (MSR-VTT, YouCook2 and EPIC-KITCHENS)

International Migration, Integration and Social Cohesion online publications

On Semantic Similarity in Video Retrieval

https://pure.uva.nl/ws/files/72607899/2103.10095.pdf

On Semantic Similarity in Video Retrieval

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International Migration, Integration and Social Cohesion online publications