Text-Driven Video Acceleration: A Weakly-Supervised Reinforcement Learning Method
Author:
Affiliation:
1. Computer Science Department, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
2. Department of Informatics, Universidade Federal de Viçosa, Viçosa, Brazil
3. Lancaster University, Lancaster, U.K.
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Fundação de Amparo à Pesquisa do Estado de Minas Gerais
Petrobras
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software
Link
http://xplorestaging.ieee.org/ielx7/34/10008914/09729633.pdf?arnumber=9729633
Reference61 articles.
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2. Personalizing Fast-Forward Videos Based on Visual and Textual Features from Social Network
3. Deep Reinforcement Learning with Double Q-Learning
4. A Weighted Sparse Sampling and Smoothing Frame Transition Approach for Semantic Fast-Forward First-Person Videos
5. Glove: Global Vectors for Word Representation
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