One-shot Talking Face
| Property | Value |
|---|---|
| Author | camenduru |
| Paper | AAAI 2022 Publication |
| Framework | PyTorch (>= 1.8) |
| License | Research License |
What is one-shot-talking-face?
One-shot-talking-face is an advanced AI model that generates realistic talking face animations from a single reference image and audio input. Developed by researchers and presented at AAAI 2022, it utilizes audio-visual correlation learning to create natural facial movements synchronized with speech.
Implementation Details
The model is built on PyTorch and requires specific components including OpenFace for initial pose extraction. It employs the CMU phoneset for phoneme representation and combines technologies from First Order Motion Model and imaginaire frameworks. The implementation requires Python 3.6+ and includes sophisticated audio-visual processing pipelines.
- Single image reference system
- Audio-driven facial animation
- CMU phoneset integration
- OpenFace pose extraction
- Pretrained checkpoint availability
Core Capabilities
- Generate realistic talking face animations from single reference image
- Process and synchronize audio input with facial movements
- Extract and utilize phoneme information
- Maintain identity consistency from reference image
- Support custom audio input processing
Frequently Asked Questions
Q: What makes this model unique?
This model's ability to generate realistic talking face animations from just one reference image sets it apart. It uses advanced audio-visual correlation learning techniques to maintain consistency between facial movements and speech.
Q: What are the recommended use cases?
The model is ideal for research purposes, content creation, and applications requiring realistic talking head generation from single images. It's particularly useful in scenarios where multiple reference images aren't available.
