Inspired by the success of WaveNet in multi-subject speech synthesis, we propose a novel neural network based on causal convolutions for multi-subject motion modeling and generation. The network can capture the intrinsic characteristics of the motion of different subjects, such as the influence of skeleton scale variation on motion style. Moreover, after fine-tuning the network using a small motion dataset for a novel skeleton that is not included in the training dataset, it is able to synthesize high-quality motions with a personalized style for the novel skeleton. The experimental results demonstrate that our network can model the intrinsic characteristics of motions well and can be applied to various motion modeling and synthesis tasks.

翻译：受WaveNet在多主体语音合成领域成功的启发，我们提出了一种基于因果卷积的新型神经网络，用于多主体运动建模与生成。该网络能够捕获不同主体运动的固有特征，例如骨骼尺寸变化对运动风格的影响。此外，通过使用针对训练数据集中未包含的新型骨骼的小型运动数据集对网络进行微调，该网络能够合成具有个性化风格的高质量运动。实验结果表明，我们的网络能够很好地建模运动的固有特征，并可应用于各种运动建模与合成任务。