[Resource] GitHub - fudan-generative-vision/hallo: Hallo: Hierarchical Audio-Driven Visual Synthesis for Portrait Image Animation

Researchers have made significant strides in creating lifelike animated portraits that respond to spoken words. To achieve this, they've developed a novel approach that ensures facial movements, lip sync, and pose changes are meticulously coordinated and visually stunning. By ditching traditional methods that rely on intermediate facial representations, this innovative technique uses an end-to-end diffusion paradigm to generate precise and realistic animations. The proposed system integrates multiple AI components, including generative models, denoisers, and temporal alignment techniques, allowing for adaptive control over expression and pose diversity. This means that the animated portraits can be tailored to individual identities, making them more relatable and engaging. The results show significant improvements in image and video quality, lip synchronization, and motion diversity. This breakthrough has exciting implications for AI companionship, enabling the creation of more realistic and personalized digital companions that can interact with humans in a more natural and empathetic way.

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