Lipschitz-Driven Noise Robustness in VQ-AE for High-Frequency Texture Repair in ID-Specific Talking Heads

Understand

Audio-driven IDentity-specific Talking Head Generation (ID-specific THG) has shown increasing promise for applications in filmmaking and virtual reality.

• Existing approaches are generally constructed as end-to-end paradigms, and have achieved significant progress.
• However, they often struggle to capture high-frequency textures due to limited model capacity.
• To address these limitations, we adopt a simple yet efficient post-processing framework -- unlike previous studies that focus solely on end-to-end training -- guided by our theoretical insights.