Audio-guided video interpolation via human pose features

Takayuki Nakatsuka, Masatoshi Hamanaka, Shigeo Morishima

研究成果: Conference contribution

抜粋

This paper describes a method that generates in-between frames of two videos of a musical instrument being played. While image generation achieves a successful outcome in recent years, there is ample scope for improvement in video generation. The keys to improving the quality of video generation are the high resolution and temporal coherence of videos. We solved these requirements by using not only visual information but also aural information. The critical point of our method is using two-dimensional pose features to generate high-resolution in-between frames from the input audio. We constructed a deep neural network with a recurrent structure for inferring pose features from the input audio and an encoder-decoder network for padding and generating video frames using pose features. Our method, moreover, adopted a fusion approach of generating, padding, and retrieving video frames to improve the output video. Pose features played an essential role in both end-to-end training with a differentiable property and combining a generating, padding, and retrieving approach. We conducted a user study and confirmed that the proposed method is effective in generating interpolated videos.

元の言語English
ホスト出版物のタイトルVISAPP
編集者Giovanni Maria Farinella, Petia Radeva, Jose Braz
出版者SciTePress
ページ27-35
ページ数9
ISBN(電子版)9789897584022
出版物ステータスPublished - 2020
イベント15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2020 - Valletta, Malta
継続期間: 2020 2 272020 2 29

出版物シリーズ

名前VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
5

Conference

Conference15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2020
Malta
Valletta
期間20/2/2720/2/29

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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  • これを引用

    Nakatsuka, T., Hamanaka, M., & Morishima, S. (2020). Audio-guided video interpolation via human pose features. : G. M. Farinella, P. Radeva, & J. Braz (版), VISAPP (pp. 27-35). (VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications; 巻数 5). SciTePress.