One-Shot Pose-Driving Face Animation Platform
He Feng, Donglin Di, Yongjia Ma, Wei Chen, Tonghua Su

TL;DR
This paper introduces a refined face animation platform that generates expressive talking head videos from a single reference face, using an improved model and a user-friendly demo interface.
Contribution
It enhances existing face animation models with a Face Locator and Motion Frame, enabling more expressive and consistent one-shot talking head video generation.
Findings
Significantly improved video quality and expressiveness.
Effective generalization to new identities without fine-tuning.
User-friendly demo platform for quick video creation.
Abstract
The objective of face animation is to generate dynamic and expressive talking head videos from a single reference face, utilizing driving conditions derived from either video or audio inputs. Current approaches often require fine-tuning for specific identities and frequently fail to produce expressive videos due to the limited effectiveness of Wav2Pose modules. To facilitate the generation of one-shot and more consecutive talking head videos, we refine an existing Image2Video model by integrating a Face Locator and Motion Frame mechanism. We subsequently optimize the model using extensive human face video datasets, significantly enhancing its ability to produce high-quality and expressive talking head videos. Additionally, we develop a demo platform using the Gradio framework, which streamlines the process, enabling users to quickly create customized talking head videos.
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Taxonomy
TopicsFace recognition and analysis
