Reproduce “Say Anything with Any Style” on OpenResearch
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About this paper
Shuai Tan, Bin Ji, Yu Ding, Ye Pan
Researchers from Shanghai Jiao Tong University and Netease Fuxi AI Lab developed "Say Anything with Any Style" (SAAS), a framework that generates highly realistic and expressive talking face videos. It achieves this by employing discrete style representation learning and dynamic network modulation to produce diverse stylized expressions and head poses, outperforming prior methods in realism and style accuracy.
Key insights
- Discrete representation learning via a VQ-VAE with a codebook is crucial for extracting explicit, distinct, and content-agnostic speaking styles, overcoming the limitations of regressive approaches.
- Dynamically modulating network weights (HyperStyle) based on an extracted style code allows a single model to effectively adapt to various styles, improving generalizability and performance.
- Explicitly modeling and generating diverse head poses with a learned codebook, conditioned on both audio and style, significantly enhances the naturalness and coherence of synthesized talking faces.
Summary by alphaXiv.
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