  With the recent success of deep learning algorithms, many researchers have
focused on generative models for human motion animation. However, the research
community lacks a platform for training and benchmarking various algorithms,
and the animation industry needs a toolkit for implementing advanced motion
synthesizing techniques. To facilitate the study of deep motion synthesis
methods for skeleton-based human animation and their potential applications in
practical animation making, we introduce \genmotion: a library that provides
unified pipelines for data loading, model training, and animation sampling with
various deep learning algorithms. Besides, by combining Python coding in the
animation software \genmotion\ can assist animators in creating real-time 3D
character animation. Source code is available at
https://github.com/realvcla/GenMotion/.
