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

We introduce SceneDiffuser, a conditional generative model for 3D scene understanding.
SceneDiffuser provides a unified model for solving scene-conditioned generation …

This paper addresses a novel task of anticipating 3D human-object interactions (HOIs). Most
existing research on HOI synthesis lacks comprehensive whole-body interactions with …

In this paper, we present Motion-X, a large-scale 3D expressive whole-body motion dataset.
Existing motion datasets predominantly contain body-only poses, lacking facial expressions …

We introduce a method for generating realistic pedestrian trajectories and full-body
animations that can be controlled to meet user-defined goals. We draw on recent advances …

Modeling human behaviors in contextual environments has a wide range of applications in
character animation, embodied AI, VR/AR, and robotics. In real-world scenarios, humans …

Confronting the challenges of data scarcity and advanced motion synthesis in human-scene
interaction modeling we introduce the TRUMANS dataset alongside a novel HSI motion …

Modelling interactions between humans and objects in natural environments is central to
many applications including gaming, virtual and mixed reality, as well as human behavior …

Given a series of natural language descriptions, our task is to generate 3D human motions
that correspond semantically to the text, and follow the temporal order of the instructions. In …

Despite significant advancements in text-to-motion synthesis generating language-guided
human motion within 3D environments poses substantial challenges. These challenges …