AI RESEARCH
Test-Time Self-Adaptive Conditioning for Stable Audio-Driven Talking-Head Generation
arXiv CS.AI
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ArXi:2605.25488v1 Announce Type: cross Audio-driven talking-head generation has achieved remarkable progress with recent models such as AniTalker, FLOAT, and Sonic. Despite their success, most existing approaches rely on a single static reference image to condition the entire video generation process at inference stage. This static conditioning paradigm often creates a mismatch between fixed identity features and dynamically evolving facial motion, leading to identity drift, temporal inconsistency, and degraded perceptual quality. We.