ENHANCED POSE GENERATION BASED ON CONDITIONAL MODELING OF INVERSE KINEMATICS

摘要

Systems and methods are provided for enhanced pose generation based on conditional modeling of inverse kinematics. An example method includes accessing an autoencoder trained based on poses, with each pose being defined based on location information of joints, and the autoencoder being trained based on conditional information indicating positions of a subset of the joints. The autoencoder is trained to reconstruct, via a latent variable space, each pose based on the conditional information. Information specifying positions of the subset of the joints is obtained via an interactive user interface and the latent variable space is sampled. An output is generated for inclusion in the interactive user interface based on the sampling and the positions.