We propose Lodge, a network capable of generating extremely long dance
sequences conditioned on given music. We design Lodge as a two-stage coarse to
fine diffusion architecture, and propose the characteristic dance primitives
that possess significant expressiveness as intermediate representations between
two diffusion models. The first stage is global diffusion, which focuses on
comprehending the coarse-level music-dance correlation and production
characteristic dance primitives. In contrast, the second-stage is the local
diffusion, which parallelly generates detailed motion sequences under the
guidance of the dance primitives and choreographic rules. In addition, we
propose a Foot Refine Block to optimize the contact between the feet and the
ground, enhancing the physical realism of the motion. Our approach can
parallelly generate dance sequences of extremely long length, striking a
balance between global choreographic patterns and local motion quality and
expressiveness. Extensive experiments validate the efficacy of our method.

提出了 Lodge，一种能够根据给定的音乐生成非常长的舞蹈序列的网络。Lodge 被设计为一个两阶段的粗粒度到细粒度的扩散架构，并提出了具有显著表现力的特征舞蹈基元，作为两个扩散模型之间的中间表示。