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

Human motion generation, a cornerstone technique in animation and video production, has
widespread applications in various tasks like text-to-motion and music-to-dance. Previous …

We present TeSMo, a text-controlled scene-aware motion generation method based on
denoising diffusion models. Previous text-to-motion methods focus on characters in isolation …

We introduce a novel Stylized Motion Diffusion model, dubbed SMooDi, to generate stylized
motion driven by content texts and style motion sequences. Unlike existing methods that …

The focus of this paper is 3D motion editing. Given a 3D human motion and a textual
description of the desired modification, our goal is to generate an edited motion as …

Given the remarkable results of motion synthesis with diffusion models, a natural question
arises: how can we effectively leverage these models for motion editing? Existing diffusion …

Crowd Motion Generation is essential in entertainment industries such as animation and
games as well as in strategic fields like urban simulation and planning. This new task …

With the release of large-scale motion datasets with textual annotations, the task of
establishing a robust latent space for language and 3D human motion has recently …

Generating human-object interactions (HOIs) is critical with the tremendous advances of
digital avatars. Existing datasets are typically limited to humans interacting with a single …

Human motion generation is a cut-edge area of research in generative computer vision, with
promising applications in video creation, game development, and robotic manipulation. The …