TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Papers/Lodge++: High-quality and Long Dance Generation with Vivid...

Lodge++: High-quality and Long Dance Generation with Vivid Choreography Patterns

Ronghui Li, Hongwen Zhang, Yachao Zhang, Yuxiang Zhang, Youliang Zhang, Jie Guo, Yan Zhang, Xiu Li, Yebin Liu

2024-10-27Motion Synthesis
PaperPDF

Abstract

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.

Results

TaskDatasetMetricValueModel
Pose TrackingFineDanceBAS0.2423Lodge++
Pose TrackingFineDancefid_k40.77Lodge++
Motion SynthesisFineDanceBAS0.2423Lodge++
Motion SynthesisFineDancefid_k40.77Lodge++
10-shot image generationFineDanceBAS0.2423Lodge++
10-shot image generationFineDancefid_k40.77Lodge++
3D Human Pose TrackingFineDanceBAS0.2423Lodge++
3D Human Pose TrackingFineDancefid_k40.77Lodge++

Related Papers

DeepGesture: A conversational gesture synthesis system based on emotions and semantics2025-07-03VolumetricSMPL: A Neural Volumetric Body Model for Efficient Interactions, Contacts, and Collisions2025-06-29DuetGen: Music Driven Two-Person Dance Generation via Hierarchical Masked Modeling2025-06-23PlanMoGPT: Flow-Enhanced Progressive Planning for Text to Motion Synthesis2025-06-22Motion-R1: Chain-of-Thought Reasoning and Reinforcement Learning for Human Motion Generation2025-06-12DanceChat: Large Language Model-Guided Music-to-Dance Generation2025-06-12MotionRAG-Diff: A Retrieval-Augmented Diffusion Framework for Long-Term Music-to-Dance Generation2025-06-03MotionPro: A Precise Motion Controller for Image-to-Video Generation2025-05-26