Lodge++: High-quality and Long Dance Generation with Vivid Choreography Patterns
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Abstract (arXiv)
We propose Lodge++, a choreography framework to generate high-quality, ultra-long, and vivid dances given the music and desired genre. To handle the challenges in computational efficiency, the learning of complex and vivid global choreography patterns, and the physical quality of local dance movements, Lodge++ adopts a two-stage strategy to produce dances from coarse to fine. In the first stage, a global choreography network is designed to generate coarse-grained dance primitives that capture complex global choreography patterns. In the second stage, guided by these dance primitives, a primitive-based dance diffusion model is proposed to further generate high-quality, long-sequence dances in parallel, faithfully adhering to the complex choreography patterns. Additionally, to improve the physical plausibility, Lodge++ employs a penetration guidance module to resolve character self-penetration, a foot refinement module to optimize foot-ground contact, and a multi-genre discriminator to maintain genre consistency throughout the dance. Lodge++ is validated by extensive experiments, which show that our method can rapidly generate ultra-long dances suitable for various dance genres, ensuring well-organized global choreography patterns and high-quality local motion.
Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Builds on 62 of its 105 references that are in the map. First posted on arXiv 27 Oct 2024.
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62 of 105 references.
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50 most cited of 62 All 62 (JSON)
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Citing papers per year: 2024: 1; 2025: 13; 2026: 7.
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- 2025TCDiff++: An End-to-end Trajectory-Controllable Diffusion Model for Harmonious Music-Driven Group Choreography23 Jun 2025
- 2025MotionRAG-Diff: A Retrieval-Augmented Diffusion Framework for Long-Term Music-to-Dance Generation3 Jun 2025
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- 2026InfiniteDance: Scalable 3D Dance Generation Towards in-the-wild Generalization10 Mar 2026
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- 2025FlowerDance: MeanFlow for Efficient and Refined 3D Dance Generation26 Nov 2025
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