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arXiv · 2604.12856

PianoFlow: Music-Aware Streaming Piano Motion Generation with Bimanual Coordination

Xuan Wang·Kai Ruan·Jiayi Han·Kaiyue Zhou·Gaoang Wang
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Abstract

Audio-driven bimanual piano motion generation requires precise modeling of complex musical structures and dynamic cross-hand coordination. However, existing methods often rely on acoustic-only representations lacking symbolic priors, employ inflexible interaction mechanisms, and are limited to computationally expensive short-sequence generation. To address these limitations, we propose PianoFlow, a flow-matching framework for precise and coordinated bimanual piano motion synthesis. Our approach strategically leverages MIDI as a privileged modality during training, distilling these structured musical priors to achieve deep semantic understanding while maintaining audio-only inference. Furthermore, we introduce an asymmetric role-gated interaction module to explicitly capture dynamic cross-hand coordination through role-aware attention and temporal gating. To enable real-time streaming generation for arbitrarily long sequences, we design an autoregressive flow continuation scheme that ensures seamless cross-chunk temporal coherence. Extensive experiments on the PianoMotion10M dataset demonstrate that PianoFlow achieves superior quantitative and qualitative performance, while accelerating inference by over 9\times compared to previous methods.

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Xuan Wang, Kai Ruan, Jiayi Han, Kaiyue Zhou, Gaoang Wang. 2026-04-14. PianoFlow: Music-Aware Streaming Piano Motion Generation with Bimanual Coordination. https://arxiv.org/abs/2604.12856

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