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 …

Conventional methods for human motion synthesis have either been deterministic or have
had to struggle with the trade-off between motion diversity vs motion quality. In response to …

We propose a method to reconstruct global human trajectories from videos in the wild. Our
optimization method decouples the camera and human motion, which allows us to place …

Estimating 3D humans from images often produces implausible bodies that lean, float, or
penetrate the floor. Such methods ignore the fact that bodies are typically supported by the …

Motion capture from sparse inertial sensors has shown great potential compared to image-
based approaches since occlusions do not lead to a reduced tracking quality and the …

The metaverse aims to build an immersive virtual reality world to support the daily life, work,
and recreation of people. In this survey, the status quo of the metaverse is investigated, and …

Three-dimensional human pose estimation has made significant advancements through the
integration of deep learning techniques. This survey provides a comprehensive review of …

Abstract 3D reconstruction of deformable (or non‐rigid) scenes from a set of monocular 2D
image observations is a long‐standing and actively researched area of computer vision and …

Develo** controllers for physics-based character simulation and control is one of the core
challenges of computer animation. In recent years, techniques that combine deep …

Egocentric 3D human pose estimation with a single head-mounted fisheye camera has
recently attracted attention due to its numerous applications in virtual and augmented reality …