论文标题
有条件的运动内部
Conditional Motion In-betweening
论文作者
论文摘要
运动中的运动（MIB）是在给定的开始和目标姿势之间产生中间骨骼运动的过程，同时保持运动的自然性，例如行走时的周期性脚步运动。尽管最先进的MIB方法能够产生稀疏的钥匙置的合理动作，但它们通常缺乏产生满足实际应用所需语义环境的动作的可控性。我们专注于可以使用统一模型处理姿势或语义条件的MIB任务的方法。我们还提出了一种运动增强方法，通过在平滑轨迹上定义分布来提高姿势条件运动产生的质量。我们提出的方法在姿势预测错误中优于现有的最新MIB方法，同时提供了额外的可控性。
Motion in-betweening (MIB) is a process of generating intermediate skeletal movement between the given start and target poses while preserving the naturalness of the motion, such as periodic footstep motion while walking. Although state-of-the-art MIB methods are capable of producing plausible motions given sparse key-poses, they often lack the controllability to generate motions satisfying the semantic contexts required in practical applications. We focus on the method that can handle pose or semantic conditioned MIB tasks using a unified model. We also present a motion augmentation method to improve the quality of pose-conditioned motion generation via defining a distribution over smooth trajectories. Our proposed method outperforms the existing state-of-the-art MIB method in pose prediction errors while providing additional controllability.
