Summary of Controllable Talking Face Generation by Implicit Facial Keypoints Editing, By Dong Zhao and Jiaying Shi and Wenjun Li and Shudong Wang and Shenghui Xu and Zhaoming Pan
Controllable Talking Face Generation by Implicit Facial Keypoints Editing
by Dong Zhao, Jiaying Shi, Wenjun Li, Shudong Wang, Shenghui Xu, Zhaoming Pan
First submitted to arxiv on: 5 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel audio-driven talking face generation method, called ControlTalk, has been proposed to control face expression deformation based on driven audio. This approach can construct head pose and facial expressions, including lip motion, for both single images or sequential video inputs in a unified manner. The method utilizes a pre-trained video synthesis renderer and proposes a lightweight adaptation to achieve precise and naturalistic lip synchronization while enabling quantitative control over mouth opening shape. ControlTalk outperforms state-of-the-art performance on widely used benchmarks, including HDTF and MEAD, and demonstrates remarkable generalization capabilities in expression deformation across same-ID and cross-ID scenarios. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ControlTalk is a new way to make talking faces that can be controlled by audio. This means you can use sounds to change the face’s expression and mouth movement. The method uses a special video generation model and makes it easier to adjust for different audio inputs. ControlTalk does better than other methods on tests like HDTF and MEAD, and can even work with faces from different people or languages. |
Keywords
» Artificial intelligence » Generalization
