克栄 渋木

VarGes: Improving Variation in Co-Speech 3D Gesture Generation via StyleCLIPS

2025 · arXiv (Cornell University)

Generating expressive and diverse human gestures from audio is crucial in fields like human-computer interaction, virtual reality, and animation. Though existing methods have achieved remarkable performance, they often exhibit limitations due to constrained dataset diversity …