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| Authors | Andrew Zisserman, Amir Jamaludin, Joon Son Chung |
| Journal/Conference Name | International Journal of Computer Vision |
| Paper Category | Artificial Intelligence |
| Paper Abstract | We present a method for generating a video of a talking face. The method takes as inputs (i) still images of the target face, and (ii) an audio speech segment; and outputs a video of the target face lip synched with the audio. The method runs in real time and is applicable to faces and audio not seen at training time. To achieve this we propose an encoder-decoder CNN model that uses a joint embedding of the face and audio to generate synthesised talking face video frames. The model is trained on tens of hours of unlabelled videos. We also show results of re-dubbing videos using speech from a different person. |
| Date of publication | 2017 |
| Code Programming Language | Matlab |
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