Text2Action: Generative Adversarial Synthesis from Language to Action
Text2Action: Generative Adversarial Synthesis from Language to Action
In this paper, we propose a generative model which learns the relationship between language and human action in order to generate a human action sequence given a sentence describing human behavior. The proposed generative model is a generative adversarial network (GAN), which is based on the sequence to sequence (SEQ2SEQ) …