A Dynamic Frame Selection Framework for Fast Video Recognition

IEEE transactions on pattern analysis and machine intelligence, pp. 1-1, 2020.

Cited by: 0|Bibtex|Views32|DOI:https://doi.org/10.1109/TPAMI.2020.3029425
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Other Links: pubmed.ncbi.nlm.nih.gov|academic.microsoft.com

Abstract:

We introduce AdaFrame, a conditional computation framework that adaptively selects relevant frames on a per-input basis for fast video recognition. AdaFrame, which contains a Long Short-Term Memory augmented with a global memory to provide context information, operates as an agent to interact with video sequences aiming to search over tim...More

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