Estimating human pose and shape from monocular images is a long-standing problem in
computer vision. Since the release of statistical body models, 3D human mesh recovery has …

Real-time sensing and modeling of the human body, especially the hands, is an important
research endeavor for various applicative purposes such as in natural human computer …

Most of the previous image-based 3D human pose and mesh estimation methods estimate
parameters of the human mesh model from an input image. However, directly regressing the …

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 …

Humans intuitively understand that inanimate objects do not move by themselves, but that
state changes are typically caused by human manipulation (eg, the opening of a book). This …

Abstract Analysis of hand-hand interactions is a crucial step towards better understanding
human behavior. However, most researches in 3D hand pose estimation have focused on …

Despite great progress in 3D pose estimation from single-view images or videos, it remains
a challenging task due to the substantial depth ambiguity and severe self-occlusions …

Estimating 3D hand pose from single RGB images is a highly ambiguous problem that relies
on an unbiased training dataset. In this paper, we analyze cross-dataset generalization …

To understand how people look, interact, or perform tasks, we need to quickly and
accurately capture their 3D body, face, and hands together from an RGB image. Most …