# Probabilistic Character Motion Synthesis using a Hierarchical Deep Latent Variable Model

arXiv: https://arxiv.org/abs/2010.09950 · HTML: https://mlsanity.com/paper/2010.09950/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Oct 2020.

## Built on by (most cited first, 16 of 16)

- [HuMoR: 3D Human Motion Model for Robust Pose Estimation](https://mlsanity.com/paper/2105.04668/) (2021)
- [Single Motion Diffusion](https://mlsanity.com/paper/2302.05905/) (2023)
- [MoDi: Unconditional Motion Synthesis from Diverse Data](https://mlsanity.com/paper/2206.08010/) (2022)
- [Estimating Body and Hand Motion in an Ego-sensed World](https://mlsanity.com/paper/2410.03665/) (2024)
- [Rhythm is a Dancer: Music-Driven Motion Synthesis with Global Structure](https://mlsanity.com/paper/2111.12159/) (2021)
- [Dyn-HaMR: Recovering 4D Interacting Hand Motion from a Dynamic Camera](https://mlsanity.com/paper/2412.12861/) (2024)
- [GAN-based Reactive Motion Synthesis with Class-aware Discriminators for Human-human Interaction](https://mlsanity.com/paper/2110.00380/) (2021)
- [TrajeVAE: Controllable Human Motion Generation from Trajectories](https://mlsanity.com/paper/2104.00351/) (2021)
- [Graph-based Normalizing Flow for Human Motion Generation and Reconstruction](https://mlsanity.com/paper/2104.03020/) (2021)
- [4DHumanOutfit: a multi-subject 4D dataset of human motion sequences in varying outfits exhibiting large displacements](https://mlsanity.com/paper/2306.07399/) (2023)
- [LEAD: Latent Realignment for Human Motion Diffusion](https://mlsanity.com/paper/2410.14508/) (2024)
- [Learned Neural Physics Simulation for Articulated 3D Human Pose Reconstruction](https://mlsanity.com/paper/2410.12023/) (2024)
- [A structured latent space for human body motion generation](https://mlsanity.com/paper/2106.04387/) (2021)
- [Representing motion as a sequence of latent primitives, a flexible approach for human motion modelling](https://mlsanity.com/paper/2206.13142/) (2022)
- [Diverse Motion In-betweening with Dual Posture Stitching](https://mlsanity.com/paper/2303.14457/) (2023)
- [Context-Aware Autoregressive Diffusion for Gloss-Wise Sign Language Production](https://mlsanity.com/paper/2606.21234/) (2026)

## Abstract (arXiv)

We present a probabilistic framework to generate character animations based on weak control signals, such that the synthesized motions are realistic while retaining the stochastic nature of human movement. The proposed architecture, which is designed as a hierarchical recurrent model, maps each sub-sequence of motions into a stochastic latent code using a variational autoencoder extended over the temporal domain. We also propose an objective function which respects the impact of each joint on the pose and compares the joint angles based on angular distance. We use two novel quantitative protocols and human qualitative assessment to demonstrate the ability of our model to generate convincing and diverse periodic and non-periodic motion sequences without the need for strong control signals.