Local-Global Video-Text Interactions for Temporal Grounding

CVPR, pp. 10807-10816, 2020.

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We have presented a novel local-global video-text interaction algorithm for text-to-video temporal grounding via constituent semantic phrase extraction

Abstract:

This paper addresses the problem of text-to-video temporal grounding, which aims to identify the time interval in a video semantically relevant to a text query. We tackle this problem using a novel regression-based model that learns to extract a collection of mid-level features for semantic phrases in a text query, which corresponds to ...More

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