Researchers in human–robot collaboration have extensively studied methods for inferring
human intentions and predicting their actions, as this is an important precursor for robots to …

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 …

Abstract We introduce Efficient Motion Diffusion Model (EMDM) for fast and high-quality
human motion generation. Current state-of-the-art generative diffusion models have …

Text-conditioned human motion generation has experienced significant advancements with
diffusion models trained on extensive motion capture data and corresponding textual …

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 …

Synthesizing semantic-aware, long-horizon, human-object interaction is critical to simulate
realistic human behaviors. In this work, we address the challenging problem of generating …

Controllable human motion synthesis is essential for applications in AR/VR, gaming and
embodied AI. Existing methods often focus solely on either language or full trajectory control …

Humans commonly work with multiple objects in daily life and can intuitively transfer
manipulation skills to novel objects by understanding object functional regularities. However …

The intimate entanglement between objects affordances and human poses is of large
interest, among others, for behavioural sciences, cognitive psychology, and Computer …

Understanding how humans cooperatively rearrange household objects is critical for VR/AR
and human-robot interaction. However, in-depth studies on modeling these behaviors are …