Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases
such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles …

The paradigm of Industry 5.0 pushes the transition from the traditional to a novel, smart,
digital, and connected industry, where well-being is key to enhance productivity, optimize …

Denoising diffusion models hold great promise for generating diverse and realistic human
motions. However, existing motion diffusion models largely disregard the laws of physics in …

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 present AIST++, a new multi-modal dataset of 3D dance motion and music, along with
FACT, a Full-Attention Cross-modal Transformer network for generating 3D dance motion …

This paper presents a high-quality human motion prediction method that accurately predicts
future human poses given observed ones. Our method is based on the observation that a …

We propose novel dynamic multiscale graph neural networks (DMGNN) to predict 3D
skeleton-based human motions. The core idea of DMGNN is to use a multiscale graph to …

Generating speech-consistent body and gesture movements is a long-standing problem in
virtual avatar creation. Previous studies often synthesize pose movement in a holistic …

How can we animate 3D-characters from a movie script or move robots by simply telling
them what we would like them to do?" How unstructured and complex can we make a …

Predicting future motion based on historical motion sequence is a fundamental problem in
computer vision, and it has wide applications in autonomous driving and robotics. Some …