Human action generation

Yan et al. (2019) CSGN:

"When the dancer is stepping, jumping and spinning on the stage, attentions of all audiences are attracted by the streamof the fluent and graceful movements. Building a model that is capable of dancing is as fascinating a task as appreciating the performance itself. In this paper, we aim to generate long-duration human actions represented as skeleton sequences, e.g. those that cover the entirety of a dance, with hundreds of moves and countless possible combinations."

<span style="color:grey; opacity: 0.6">( Image credit: Convolutional Sequence Generation for Skeleton-Based Action Synthesis )</span>