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 …

We address the problem of generating realistic 3D motions of humans interacting with
objects in a scene. Our key idea is to create a neural interaction field attached to a specific …

Most existing monocular 3D pose estimation approaches only focus on a single body part,
neglecting the fact that the essential nuance of human motion is conveyed through a concert …

Learning to generate diverse scene-aware and goal-oriented human motions in 3D scenes
remains challenging due to the mediocre characters of the existing datasets on Human …

We have recently seen tremendous progress in diffusion advances for generating realistic
human motions. Yet, they largely disregard the multi-human interactions. In this paper, we …

This paper presents a novel approach to generating the 3D motion of a human interacting
with a target object, with a focus on solving the challenge of synthesizing long-range and …

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 …

We propose CG-HOI the first method to address the task of generating dynamic 3D human-
object interactions (HOIs) from text. We model the motion of both human and object in an …