The intrinsic rotation invariance lies at the core of matching point clouds with handcrafted
descriptors. However, it is widely despised by recent deep matchers that obtain the rotation …

Abstract We present Multi-Garment Network (MGN), a method to predict body shape and
clothing, layered on top of the SMPL model from a few frames (1-8) of a video. Several …

This paper describes how to obtain accurate 3D body models and texture of arbitrary people
from a single, monocular video in which a person is moving. Based on a parametric body …

Human performance capture is a highly important computer vision problem with many
applications in movie production and virtual/augmented reality. Many previous performance …

We present the first real-time human performance capture approach that reconstructs dense,
space-time coherent deforming geometry of entire humans in general everyday clothing …

We present a novel method for high detail-preserving human avatar creation from
monocular video. A parameterized body model is refined and optimized to maximally …

We present Octopus, a learning-based model to infer the personalized 3D shape of people
from a few frames (1-8) of a monocular video in which the person is moving with a …

We present a novel method for real-time pose and shape reconstruction of two strongly
interacting hands. Our approach is the first two-hand tracking solution that combines an …

Pose estimation, tracking, and action recognition of articulated objects from depth images
are important and challenging problems, which are normally considered separately. In this …

We present a system that builds 3D models of non-rigidly moving surfaces from scratch in
real time using a single RGB-D stream. Our solution is based on the variational level set …