{"ID":6497598,"CreatedAt":"2026-07-13T01:19:40.13847098Z","UpdatedAt":"2026-07-14T01:36:59.12045529Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.09581","arxiv_id":"2607.09581","title":"Wan-Dancer: A Hierarchical Framework for Minute-scale Coherent Music-to-Dance Generation","abstract":"Generating long-duration, high-definition, and rhythmically synchronized dance videos directly from music remains a significant challenge, primarily due to the temporal constraints of current diffusion models, which typically fail beyond 20 seconds. Existing approaches, whether they rely on intermediate 3D skeletons or on end-to-end video synthesis, suffer from temporal drift, identity inconsistency, and repetitive motion patterns when extended to longer horizons. To address these limitations, we propose a novel hierarchical framework for minute-scale coherent music-to-dance generation. Our method decouples the process into global keyframe planning and local temporal refinement, leveraging full-track musical context to ensure long-range coherence. Key innovations include dynamic frame rate adaptation via time-mapped RoPE embeddings for precise alignment, an optical-flow-based loss function to enhance motion continuity, and motion-speed control to preserve high-fidelity details during rapid movements. Extensive experiments demonstrate that our framework surpasses the conventional duration barrier, generating stable, 720p/30fps videos exceeding one minute with superior temporal stability. Furthermore, the model exhibits robust versatility across five distinct dance genres, conditioned on both audio and textual prompts, establishing a new state-of-the-art in coherent, long-form dance video synthesis.","short_abstract":"Generating long-duration, high-definition, and rhythmically synchronized dance videos directly from music remains a significant challenge, primarily due to the temporal constraints of current diffusion models, which typically fail beyond 20 seconds. Existing approaches, whether they rely on intermediate 3D skeletons or...","url_abs":"https://arxiv.org/abs/2607.09581","url_pdf":"https://arxiv.org/pdf/2607.09581v1","authors":"[\"Mingyang Huang\",\"Peng Zhang\",\"Li Hu\",\"Guangyuan Wang\",\"Bang Zhang\"]","published":"2026-07-10T16:30:29Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.SD\"]","methods":"[\"Diffusion Model\"]","has_code":false}