We consider the problem of sentence specified dynamic video thumbnail generation. Given an input video and a user query sentence, the goal is to generate a video thumbnail that not only provides the preview of the video content, but also semantically corresponds to the sentence. In this paper, we propose a sentence guided temporal modulation (SGTM) mechanism that utilizes the sentence embedding to modulate the normalized temporal activations of the video thumbnail generation network. Unlike the existing state-of-the-art method that uses recurrent architectures, we propose a non-recurrent framework that is simple and allows much more parallelization. Extensive experiments and analysis on a large-scale dataset demonstrate the effectiveness of our framework.
@article{arxiv.2008.13362,
title = {Sentence Guided Temporal Modulation for Dynamic Video Thumbnail Generation},
author = {Mrigank Rochan and Mahesh Kumar Krishna Reddy and Yang Wang},
journal= {arXiv preprint arXiv:2008.13362},
year = {2020}
}