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Updated: Dec 8, 2025
11:34
High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
Published on: December 3, 2013
15.9K
Photorealistic Audio-driven Video Portraits
IEEE Transactions on Visualization and Computer Graphics
|September 17, 2020
Summary
This study introduces a new method for creating realistic video portraits driven by voice. The approach synthesizes photorealistic facial expressions from speech audio, outperforming existing methods in user studies.
Area of Science:
- Computer Vision
- Machine Learning
- Computer Graphics
Background:
- Video portraits are widely used in applications like videoconferencing and virtual training.
- Synthesizing photorealistic facial expressions from speech audio presents a significant challenge.
Purpose of the Study:
- To develop a novel method for synthesizing photorealistic video portraits driven by voice.
- To address the challenge of hallucinating plausible facial expressions from speech audio.
Main Methods:
- Utilized a parametric 3D face model to learn audio features to model parameter mapping.
- Predicted facial expression parameters from high-dimensional audio features.
- Employed a neural face renderer to generate photorealistic video portraits.
Main Results:
- The proposed method successfully synthesizes photorealistic video portraits driven by voice.
- Demonstrated generalization capabilities with various input speech audio, including text-to-speech.
- Outperformed previous general-purpose audio-driven video portrait methods in experiments and user studies.
Conclusions:
- The novel method effectively synthesizes realistic audio-driven video portraits.
- The approach offers a significant advancement in synthesizing facial expressions from speech.
- Results indicate superior realism compared to existing methods.
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