Abstract 3D human pose and shape estimation (aka``human mesh recovery'') has achieved
substantial progress. Researchers mainly focus on the development of novel algorithms …

Recent approaches to drape garments quickly over arbitrary human bodies leverage self-
supervision to eliminate the need for large training sets. However, they are designed to train …

Abstract The Skinned Multi-Person Linear (SMPL) model represents human bodies by
mapping pose and shape parameters to body meshes. However, not all pose and shape …

Many approaches to draping individual garments on human body models are realistic, fast,
and yield outputs that are differentiable with respect to the body shape on which they are …

Existing data-driven methods for draping garments over human bodies, despite being
effective, cannot handle garments of arbitrary topology and are typically not end-to-end …

While modeling people wearing tight-fitting clothing has made great strides in recent years
loose-fitting clothing remains a challenge. We propose a method that delivers realistic …

KBody is a method for fitting a low-dimensional body model to an image. It follows a predict-
and-optimize approach, relying on data-driven model estimates for the constraints that will …

The performance of existing methods for multi-person 3D pose estimation in crowded
scenes is still limited, due to the challenge of heavy overlapping among persons. Attempt to …

We present a Body Measurement network (BMnet) for estimating 3D anthropomorphic
measurements of the human body shape from silhouette images. Training of BMnet is …

Deep learning models are nowadays broadly deployed to solve an incredibly large variety of
tasks. Commonly, leveraging over the availability of" big data", deep neural networks are …