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We consider the problem of sentence specified dynamic video thumbnailgeneration. Given an input video and a user query sentence, the goal is togenerate a video thumbnail that not only provides the preview of the videocontent, but also semantically corresponds to the sentence. In this paper, wepropose a sentence guided temporal modulation (SGTM) mechanism that utilizesthe sentence embedding to modulate the normalized temporal activations of thevideo thumbnail generation network. Unlike the existing state-of-the-art methodthat uses recurrent architectures, we propose a non-recurrent framework that issimple and allows much more parallelization. Extensive experiments and analysison a large-scale dataset demonstrate the effectiveness of our framework.

Sentence Guided Temporal Modulation for Dynamic Video Thumbnail Generation