Conference item
Out of time: automated lip sync in the wild
- Abstract:
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The goal of this work is to determine the audio-video synchronisation between mouth motion and speech in a video.
We propose a two-stream ConvNet architecture that enables the mapping between the sound and the mouth images to be trained end-to-end from unlabelled data. The trained network is used to determine the lip-sync error in a video.
We apply the network to two further tasks: active speaker detection and lip reading. On both tasks we set a new state-of-the-art on standard benchmark datasets.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted manuscript
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- Files:
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(pdf, 3.2MB)
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- Publisher copy:
- 10.1007/978-3-319-54427-4_19
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Authors
Funding
Bibliographic Details
- Publisher:
- Springer Publisher's website
- Publication date:
- 2017-03-05
- Acceptance date:
- 2016-05-27
- DOI:
- Pubs id:
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pubs:656453
- URN:
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uri:6bdd4768-6fbd-40ac-8efc-edca8a0325b3
- UUID:
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uuid:6bdd4768-6fbd-40ac-8efc-edca8a0325b3
- Local pid:
- pubs:656453
Terms of use
- Copyright holder:
- Springer International Publishing AG
- Copyright date:
- 2017
- Notes:
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© Springer International Publishing AG 2017
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