Human motion generation aims to generate natural human pose sequences and shows
immense potential for real-world applications. Substantial progress has been made recently …

Though the advancement of pre-trained large language models unfolds, the exploration of
building a unified model for language and other multimodal data, such as motion, remains …

Text-to-image models offer unprecedented freedom to guide creation through natural
language. Yet, it is unclear how such freedom can be exercised to generate images of …

Human motion modeling is important for many modern graphics applications, which typically
require professional skills. In order to remove the skill barriers for laymen, recent motion …

In this work, we investigate a simple and must-known conditional generative framework
based on Vector Quantised-Variational AutoEncoder (VQ-VAE) and Generative Pre-trained …

We study a challenging task, conditional human motion generation, which produces
plausible human motion sequences according to various conditional inputs, such as action …

Dance is an important human art form, but creating new dances can be difficult and time-
consuming. In this work, we introduce Editable Dance GEneration (EDGE), a state-of-the-art …

Denoising diffusion models hold great promise for generating diverse and realistic human
motions. However, existing motion diffusion models largely disregard the laws of physics in …

Conventional methods for human motion synthesis have either been deterministic or have
had to struggle with the trade-off between motion diversity vs motion quality. In response to …

We introduce MotionCLIP, a 3D human motion auto-encoder featuring a latent embedding
that is disentangled, well behaved, and supports highly semantic textual descriptions …