Reinforcement Learning for Weakly Supervised Temporal Grounding of Natural Language in Untrimmed Videos

MM '20: The 28th ACM International Conference on Multimedia Seattle WA USA October, 2020, pp. 1283-1291, 2020.

Cited by: 0|Bibtex|Views18|DOI:https://doi.org/10.1145/3394171.3413862
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Abstract:

Temporal grounding of natural language in untrimmed videos is a fundamental yet challenging multimedia task facilitating cross-media visual content retrieval. We focus on the weakly supervised setting of this task that merely accesses to coarse video-level language description annotation without temporal boundary, which is more consistent...More

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