We propose a new framework for gesture generation, aiming to allow data-driven approaches to produce more semantically rich gestures. Our approach first predicts whether to gesture, followed by a prediction of the gesture properties. Those properties are then used as conditioning for a modern probabilistic gesture-generation model capable of high-quality output. This empowers the approach to generate gestures that are both diverse and representational.
翻译:我们提出了一个新的手势生成框架,目的是让数据驱动方法产生更丰富的体力化手势。 我们的方法首先预测是否做出手势,然后预测手势的属性。 这些属性随后被用作现代手势生成模型的前提条件,该模型能够产生高质量的产出。 这赋予了方法产生多样和代表性的手势的能力。