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.
@article{arxiv.2407.08949,
title = {One-Shot Pose-Driving Face Animation Platform},
author = {He Feng and Donglin Di and Yongjia Ma and Wei Chen and Tonghua Su},
journal= {arXiv preprint arXiv:2407.08949},
year = {2024}
}