VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing in the Wild

We present VideoReTalking, a new system to edit the faces of a real-world talking head video according to input audio, producing a high-quality and lip-syncing output video even with a different emotion. Our system disentangles this objective into three sequential tasks:

(1) face video generation with a canonical expression
(2) audio-driven lip-sync and
(3) face enhancement for improving photo-realism.

Given a talking-head video, we first modify the expression of each frame according to the same expression template using the expression editing network, resulting in a video with the canonical expression. This video, together with the given audio, is then fed into the lip-sync network to generate a lip-syncing video. Finally, we improve the photo-realism of the synthesized faces through an identity-aware face enhancement network and post-processing. We use learning-based approaches for all three steps and all our modules can be tackled in a sequential pipeline without any user intervention.

Citation

If you find our work useful in your research, please consider citing:

@misc{cheng2022videoretalking,
        title={VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild}, 
        author={Kun Cheng and Xiaodong Cun and Yong Zhang and Menghan Xia and Fei Yin and Mingrui Zhu and Xuan Wang and Jue Wang and Nannan Wang},
        year={2022},
        eprint={2211.14758},
        archivePrefix={arXiv},
        primaryClass={cs.CV}
  }

Acknowledgement

Thanks to Wav2Lip, PIRenderer, GFP-GAN, GPEN, ganimation_replicate, STIT for sharing their code.

Related Work

• StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN (ECCV 2022)
• CodeTalker: Speech-Driven 3D Facial Animation with Discrete Motion Prior (CVPR 2023)
• SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation (CVPR 2023)
• DPE: Disentanglement of Pose and Expression for General Video Portrait Editing (CVPR 2023)
• 3D GAN Inversion with Facial Symmetry Prior (CVPR 2023)
• T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations (CVPR 2023)

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