Higgsfield AI's Soul ID technology has achieved a breakthrough in character dynamic feature capture through a neural network model built from multi-angle photo training. After the user uploads more than 10 photos containing different micro-expressions, lighting conditions and angles, the 3D expression-based model constructed by the system can accurately restore more than 93% facial muscle movement features. Test data shows that the generated virtual image reaches ±1.2 degrees in the curvature of the mouth angle accuracy, and the deviation of the eye rotation trajectory is less than 2.3 pixels, and these parameters are close to the Face ID recognition accuracy standard of iPhone 14 Pro.
Application scenarios for this technology include:
- Real-time driving of 52 basic expressions implemented in Digital Split Live
- Maintains lip-synchronization error of less than 0.1 seconds in cross-language video dubbing
- Maintains skin tone material consistency across different lighting conditions up to RGB ΔE<3
In 2023 A/B testing, e-commerce explainer videos generated using Soul ID increased user dwell time by 171 TP3T over live-action videos.
This answer comes from the articleHiggsfield AI: Using AI to Generate Lifelike Videos and Personalized AvatarsThe
