论文标题

音乐驱动的舞蹈再生,具有可控的钥匙姿势限制

Music-driven Dance Regeneration with Controllable Key Pose Constraints

论文作者

Pu, Junfu, Shan, Ying

论文摘要

在本文中,我们为音乐驱动的舞蹈运动综合构成了一个新颖的框架,并具有可控的关键姿势约束。与仅基于音乐产生舞蹈运动序列的方法相反,该工作的目标是综合由音乐驱动的高质量舞蹈运动以及用户执行的定制姿势。我们的模型涉及两个用于音乐和运动表示形式的单模式变压器编码器,以及用于舞蹈动作产生的跨模式变压器解码器。跨模式变压器解码器可以通过引入局部邻居位置嵌入来构成平滑舞蹈运动序列合成平滑舞蹈运动序列的能力。这种机制使解码器对关键姿势和相应位置更加敏感。我们的舞蹈合成模型通过广泛的实验在定量和定性评估上取得了令人满意的表现,这证明了我们提出的方法的有效性。

In this paper, we propose a novel framework for music-driven dance motion synthesis with controllable key pose constraint. In contrast to methods that generate dance motion sequences only based on music without any other controllable conditions, this work targets on synthesizing high-quality dance motion driven by music as well as customized poses performed by users. Our model involves two single-modal transformer encoders for music and motion representations and a cross-modal transformer decoder for dance motions generation. The cross-modal transformer decoder achieves the capability of synthesizing smooth dance motion sequences, which keeps a consistency with key poses at corresponding positions, by introducing the local neighbor position embedding. Such mechanism makes the decoder more sensitive to key poses and the corresponding positions. Our dance synthesis model achieves satisfactory performance both on quantitative and qualitative evaluations with extensive experiments, which demonstrates the effectiveness of our proposed method.

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