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 …

The development of big data technologies, which have been applied extensively in various
areas, has become one of the key factors affecting modern society, especially in the virtual …

Modeling animatable human avatars from RGB videos is a long-standing and challenging
problem. Recent works usually adopt MLP-based neural radiance fields (NeRF) to represent …

It is extremely challenging to create an animatable clothed human avatar from RGB videos,
especially for loose clothes due to the difficulties in motion modeling. To address this …

Regression-based methods have recently shown promising results in reconstructing human
meshes from monocular images. By directly map** raw pixels to model parameters, these …

Inferring human-scene contact (HSC) is the first step toward understanding how humans
interact with their surroundings. While detecting 2D human-object interaction (HOI) and …

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 …

Given an image with multiple people, our goal is to directly regress the pose and shape of all
the people as well as their relative depth. Inferring the depth of a person in an image …

Graph convolutional network (GCN) has achieved great success in single hand
reconstruction task, while interacting two-hand reconstruction by GCN remains unexplored …

Abstract 4D human sensing and modeling are fundamental tasks in vision and graphics with
numerous applications. With the advances of new sensors and algorithms, there is an …