  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.
