PC-Talk: Precise Facial Animation Control for Audio-Driven Talking Face Generation
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915206194528256 |
|---|---|
| author | Wang, Baiqin Zhu, Xiangyu Shen, Fan Xu, Hao Lei, Zhen |
| author_facet | Wang, Baiqin Zhu, Xiangyu Shen, Fan Xu, Hao Lei, Zhen |
| contents | Recent advancements in audio-driven talking face generation have made great progress in lip synchronization. However, current methods often lack sufficient control over facial animation such as speaking style and emotional expression, resulting in uniform outputs. In this paper, we focus on improving two key factors: lip-audio alignment and emotion control, to enhance the diversity and user-friendliness of talking videos. Lip-audio alignment control focuses on elements like speaking style and the scale of lip movements, whereas emotion control is centered on generating realistic emotional expressions, allowing for modifications in multiple attributes such as intensity. To achieve precise control of facial animation, we propose a novel framework, PC-Talk, which enables lip-audio alignment and emotion control through implicit keypoint deformations. First, our lip-audio alignment control module facilitates precise editing of speaking styles at the word level and adjusts lip movement scales to simulate varying vocal loudness levels, maintaining lip synchronization with the audio. Second, our emotion control module generates vivid emotional facial features with pure emotional deformation. This module also enables the fine modification of intensity and the combination of multiple emotions across different facial regions. Our method demonstrates outstanding control capabilities and achieves state-of-the-art performance on both HDTF and MEAD datasets in extensive experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_14295 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PC-Talk: Precise Facial Animation Control for Audio-Driven Talking Face Generation Wang, Baiqin Zhu, Xiangyu Shen, Fan Xu, Hao Lei, Zhen Computer Vision and Pattern Recognition Artificial Intelligence Recent advancements in audio-driven talking face generation have made great progress in lip synchronization. However, current methods often lack sufficient control over facial animation such as speaking style and emotional expression, resulting in uniform outputs. In this paper, we focus on improving two key factors: lip-audio alignment and emotion control, to enhance the diversity and user-friendliness of talking videos. Lip-audio alignment control focuses on elements like speaking style and the scale of lip movements, whereas emotion control is centered on generating realistic emotional expressions, allowing for modifications in multiple attributes such as intensity. To achieve precise control of facial animation, we propose a novel framework, PC-Talk, which enables lip-audio alignment and emotion control through implicit keypoint deformations. First, our lip-audio alignment control module facilitates precise editing of speaking styles at the word level and adjusts lip movement scales to simulate varying vocal loudness levels, maintaining lip synchronization with the audio. Second, our emotion control module generates vivid emotional facial features with pure emotional deformation. This module also enables the fine modification of intensity and the combination of multiple emotions across different facial regions. Our method demonstrates outstanding control capabilities and achieves state-of-the-art performance on both HDTF and MEAD datasets in extensive experiments. |
| title | PC-Talk: Precise Facial Animation Control for Audio-Driven Talking Face Generation |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2503.14295 |