Motion retargetting refers to the process of adapting the motion of a source character to a target. This paper presents a motion retargetting model based on temporal dilated convolutions. In an unsupervised manner, the model generates realistic motions for various humanoid characters. The retargetted motions not only preserve the high‐frequency detail of the input motions but also produce natural and stable trajectories despite the skeleton size differences between the source and target. Extensive experiments are made using a 3D character motion dataset and a motion capture dataset. Both qualitative and quantitative comparisons against prior methods demonstrate the effectiveness and robustness of our method.

中文翻译：

---

基于扩张卷积和骨架特定损失函数的运动重定向

运动重定向是指使源角色的运动适应目标的过程。本文提出了一种基于时间扩张卷积的运动重定向模型。该模型以无监督的方式为各种人形角色生成逼真的动作。尽管源和目标之间的骨架大小不同，重定向的运动不仅保留了输入运动的高频细节，而且还产生了自然而稳定的轨迹。使用 3D 角色运动数据集和运动捕捉数据集进行了大量实验。与先前方法的定性和定量比较都证明了我们方法的有效性和稳健性。