SOURCE-LINKED INTELLIGENCE
GestureFAR: Streaming Co-Speech Gesture Generation with Flow Autoregression
Generating natural co-speech gestures from streaming speech is essential for embodied conversational agents, where motion must be produced while a user is still speaking. Recent streaming gesture systems make online generation possible by autoregressing over discrete motion tokens, but this design compresses high-dimensional continuous motion into finite codebooks and can limit the realism and diversity of generated gestures. To preserve both causality and continuous expressiveness, we propose \textbf{GestureFAR}, a flow-autoregressive framework for streaming co-speech gesture generation. Firs
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T10:07:45.000Z
First collected: 2026-09-23T13:51:27.104Z. This is not the publication date.