In recent years generative models have been a viral topic within the field of deep learning. First, generate model used to generate the picture and then temporal feature comes into this new area of research and many researches have been done to generate pixel-based video. Alongside generative models, human action recognition is a well studied and reliable task in the deep learning field, the goal of this task is to determine the type of action of human activity based on the sequence of moving skeleton by using the spatiotemporal features, but in this work, we tried to do this task reversely, generate moving human skeleton by choosing action type.