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

Recent advances in text-to-motion generation using diffusion and autoregressive models
have shown promising results. However these models often suffer from a trade-off between …

This paper addresses new methodologies to deal with the challenging task of generating
dynamic Human-Object Interactions from textual descriptions (Text2HOI). While most …

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 …

Generating human-human motion interactions conditioned on textual descriptions is a very
useful application in many areas such as robotics gaming animation and the metaverse …

Text-to-motion generation holds potential for film, gaming, and robotics, yet current methods
often prioritize short motion generation, making it challenging to produce long motion …

This paper introduces the first text-guided work for generating the sequence of hand-object
interaction in 3D. The main challenge arises from the lack of labeled data where existing …

Human motion understanding is a fundamental task with diverse practical applications,
facilitated by the availability of large-scale motion capture datasets. Recent studies focus on …

In this study, we introduce T2M-HiFiGPT, a novel conditional generative framework for
synthesizing human motion from textual descriptions. This framework is underpinned by a …

In motion generation, controllability as well as generation quality and speed is becoming
more and more important. There are various motion editing tasks, such as in-betweening …