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arxiv 1705.02966 v2 pith:CQCIAZBD submitted 2017-05-08 cs.CV

Joon Son Chung , Amir Jamaludin , Andrew Zisserman This is my paper
classification cs.CV
keywords faceaudiomethodvideomodelspeechtalkingtarget
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 1 Pith paper

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  1. MoDiT: Learning Highly Consistent 3D Motion Coefficients with Diffusion Transformer for Talking Head Generation

    cs.CV 2025-07 conditional novelty 5.0 of 10

    MoDiT, a diffusion transformer conditioned on 3DMM coefficients and Wav2Lip references, produces talking-head videos with improved same-identity lip sync and more natural blinks in its reported benchmarks.

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