Human motion generation stands as a significant pursuit in generative computer vision,
while achieving long-sequence and efficient motion generation remains challenging. Recent …

Text-to-motion generation is a formidable task, aiming to produce human motions that align
with the input text while also adhering to human capabilities and physical laws. While there …

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 introduce MoMask a novel masked modeling framework for text-driven 3D human
motion generation. In MoMask a hierarchical quantization scheme is employed to represent …

Music-driven group choreography poses a considerable challenge but holds significant
potential for a wide range of industrial applications. The ability to generate synchronized and …

In this work, we present Semantic Gesticulator, a novel framework designed to synthesize
realistic gestures accompanying speech with strong semantic correspondence. Semantically …

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 …

Controllable generation of 3D human motions becomes an important topic as the world
embraces digital transformation. Existing works, though making promising progress with the …

Generating realistic human motion sequences from text descriptions is a challenging task
that requires capturing the rich expressiveness of both natural language and human motion …

We introduce a novel task within the field of 3D dance generation, termed dance
accompaniment, which necessitates the generation of responsive movements from a dance …