StreamAvatar: Streaming Diffusion Models for Real-Time Interactive Human Avatars

ArXi:2512.22065v2 Announce Type: replace-cross Real-time, streaming interactive avatars represent a critical yet challenging goal in digital human research. Although diffusion-based human avatar generation methods achieve remarkable success, their non-causal architecture and high computational costs make them unsuitable for streaming. Moreover, existing interactive approaches are typically restricted to the head-and-shoulder region, limiting their ability to produce gestures and body motions.