Linguistic Descriptions of Human Motion with Generative Adversarial Seq2Seq Learning
Yusuke Goutsu Tetsunari Inamura Yusuke Goutsu Tetsunari Inamura
In this paper, we propose a generative model that learns a sequence-to-sequence (Seq2Seq) translation between human whole-body motions and linguistic descriptions by natural language. Our model merges the Seq2Seq model with the training strategy of sequence generative adversarial nets (SeqGAN), which extends a GAN framework to solve the problem that the gradient cannot pass back to the generator n...