Using independently recurrent networks for reinforcement learning based unsupervised video summarization
Author:
Funder
TUBITAK
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-020-10293-x.pdf
Reference53 articles.
1. Cai S, Zuo W, Davis LS, Zhang L (2018) Weakly-supervised video summarization using variational encoder-decoder and web prior. In: Proceedings of the European conference on computer vision (ECCV), pp 184–200
2. Casas LL, Koblents E (2019) Video summarization with lstm and deep attention models. In: International conference on multimedia modeling. Springer, pp 67–79
3. Chakraborty S, Tickoo O, Iyer R (2015) Adaptive keyframe selection for video summarization. In: 2015 IEEE winter conference on applications of computer vision. IEEE, pp 702–709
4. Chung J, Gulcehre C, Cho K, Bengio Y (2014) Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv:1412.3555
5. De Avila SEF, Lopes APB, da Luz A Jr, de Albuquerque Araújo A (2011) Vsumm: a mechanism designed to produce static video summaries and a novel evaluation method. Pattern Recognit Lett 32(1):56–68
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