Abstract Three-dimensional (3D) human pose estimation involves estimating the articulated
3D joint locations of a human body from an image or video. Due to its widespread …

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 …

We introduce HuMoR: a 3D Human Motion Model for Robust Estimation of temporal pose
and shape. Though substantial progress has been made in estimating 3D human motion …

We present PyMAF-X, a regression-based approach to recovering a parametric full-body
model from a single image. This task is very challenging since minor parametric deviation …

Human motion is fundamental to understanding behavior. Despite progress on single-image
3D pose and shape estimation, existing video-based state-of-the-art methods fail to produce …

Abstract Model-based human pose estimation is currently approached through two different
paradigms. Optimization-based methods fit a parametric body model to 2D observations in …

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 …

Abstract We introduce Pixel-aligned Implicit Function (PIFu), an implicit representation that
locally aligns pixels of 2D images with the global context of their corresponding 3D object …