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Towards Data-Driven Automatic Video Editing

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1074)


Automatic video editing involving at least the steps of selecting the most valuable footage from points of view of visual quality and the importance of action filmed; and cutting the footage into a brief and coherent visual story that would be interesting to watch is implemented in a purely data-driven manner. Visual semantic and aesthetic features are extracted by the ImageNet-trained convolutional neural network, and the editing controller is trained by an imitation learning algorithm. As a result, at test time the controller shows the signs of observing basic cinematography editing rules learned from the corpus of motion pictures masterpieces.


  • Automatic video editing
  • Convolutional neural networks
  • Reinforcement learning

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  • DOI: 10.1007/978-3-030-32456-8_39
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Correspondence to Sergey Podlesnyy .

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Podlesnyy, S. (2020). Towards Data-Driven Automatic Video Editing. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1074. Springer, Cham.

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