Web: http://arxiv.org/abs/2201.10990

Jan. 27, 2022, 2:10 a.m. | Xudong Lin, Fabio Petroni, Gedas Bertasius, Marcus Rohrbach, Shih-Fu Chang, Lorenzo Torresani

cs.CV updates on arXiv.org arxiv.org

In this paper we consider the problem of classifying fine-grained, multi-step
activities (e.g., cooking different recipes, making disparate home
improvements, creating various forms of arts and crafts) from long videos
spanning up to several minutes. Accurately categorizing these activities
requires not only recognizing the individual steps that compose the task but
also capturing their temporal dependencies. This problem is dramatically
different from traditional action classification, where models are typically
optimized on videos that span only a few seconds and that …

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