论文标题
在线运动样式转移用于交互性角色控制
Online Motion Style Transfer for Interactive Character Control
论文作者
论文摘要
运动样式转移非常希望用于游戏的运动系统。与离线同行相比，在交互式控制下对在线运动风格转移的研究有限。在这项工作中，我们提出了一个端到端神经网络，该网络可以在用户控制下实时生成不同样式的动作和转移运动样式。我们的方法消除了手工制作的相位功能的使用，并且可以轻松地训练和直接部署在游戏系统中。在实验部分中，我们从工业游戏设计至关重要的三个方面评估了我们的方法：准确性，灵活性和多样性，并且我们的模型会产生令人满意的结果。
Motion style transfer is highly desired for motion generation systems for gaming. Compared to its offline counterpart, the research on online motion style transfer under interactive control is limited. In this work, we propose an end-to-end neural network that can generate motions with different styles and transfer motion styles in real-time under user control. Our approach eliminates the use of handcrafted phase features, and could be easily trained and directly deployed in game systems. In the experiment part, we evaluate our approach from three aspects that are essential for industrial game design: accuracy, flexibility, and variety, and our model performs a satisfying result.
