MoDi: Unconditional Motion Synthesis from Diverse Data

Figure 1 . Our generative model is learned in an unsupervised setting from a diverse, unstructured and unlabeled motion dataset and yields a highly semantic, clustered, latent space that facilitates synthesis operations. An encoder and a mapping network enable the employment of real and generated motions, respectively.