JoyGen: Audio-Driven 3D Depth-Aware Talking-Face Video Editing

• URL: http://arxiv.org/abs/2501.01798v1
• Date: Fri, 03 Jan 2025 13:14:52 GMT
• Title: JoyGen: Audio-Driven 3D Depth-Aware Talking-Face Video Editing
• Authors: Qili Wang, Dajiang Wu, Zihang Xu, Junshi Huang, Jun Lv,
• Abstract summary: JoyGen is a two-stage framework for talking-face generation. In the first stage, a 3D reconstruction model and an audio2motion model predict identity and expression coefficients. In the second stage, we provide comprehensive supervision for precise lip-audio synchronization in facial generation.
• Score: 7.432808260671468
• License:
• Abstract: Significant progress has been made in talking-face video generation research; however, precise lip-audio synchronization and high visual quality remain challenging in editing lip shapes based on input audio. This paper introduces JoyGen, a novel two-stage framework for talking-face generation, comprising audio-driven lip motion generation and visual appearance synthesis. In the first stage, a 3D reconstruction model and an audio2motion model predict identity and expression coefficients respectively. Next, by integrating audio features with a facial depth map, we provide comprehensive supervision for precise lip-audio synchronization in facial generation. Additionally, we constructed a Chinese talking-face dataset containing 130 hours of high-quality video. JoyGen is trained on the open-source HDTF dataset and our curated dataset. Experimental results demonstrate superior lip-audio synchronization and visual quality achieved by our method.

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