This work introduces MotionLCM, extending controllable motion generation to a real-time
level. Existing methods for spatial-temporal control in text-conditioned motion generation …

The scaling law has been validated in various domains, such as natural language
processing (NLP) and massive computer vision tasks; however, its application to motion …

This research delves into the problem of interactive editing of human motion generation.
Previous motion diffusion models lack explicit modeling of the word-level text-motion …

Generating realistic 3D human-object interactions (HOIs) from text descriptions is a active
research topic with potential applications in virtual and augmented reality, robotics, and …

Diffusion models achieve impressive performance in human motion generation. However,
current approaches typically ignore the significance of frequency-domain information in …

Diffusion models have become a popular choice for human motion synthesis due to their
powerful generative capabilities. However, their high computational complexity and large …

Existing methods for spatial-temporal control in text-conditioned motion generation suffer
from significant runtime inefficiency. To address this issue, we first propose the motion latent …