106 citations · 255 across the 11 of their papers we have counts for
5 papers · 1 filter
TailorMe: Self-Supervised Learning of an Anatomically Constrained Volumetric Human Shape Model
Stephan Wenninger, Fabian Kemper, Ulrich Schwanecke +1
Human shape spaces have been extensively studied, as they are a core element of human shape and pose inference tasks. Classic methods for creating a human shape model register a su…
Real-time Light Estimation and Neural Soft Shadows for AR Indoor Scenarios
Alexander Sommer, Ulrich Schwanecke, Elmar Schömer
We present a pipeline for realistic embedding of virtual objects into footage of indoor scenes with focus on real-time AR applications. Our pipeline consists of two main components…
NeuralQAAD: An Efficient Differentiable Framework for High Resolution Point Cloud Compression
Nicolas Wagner, Ulrich Schwanecke
In this paper, we propose NeuralQAAD, a differentiable point cloud compression framework that is fast, robust to sampling, and applicable to high resolutions. Previous work that is…
A method for automatic forensic facial reconstruction based on dense statistics of soft tissue thickness
Thomas Gietzen, Robert Brylka, Jascha Achenbach +5
In this paper, we present a method for automated estimation of a human face given a skull remain. The proposed method is based on three statistical models. A volumetric (tetrahedra…
A Region-based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking
Henning Tjaden, Ulrich Schwanecke, Elmar Schömer +1
We propose an algorithm for real-time 6DOF pose tracking of rigid 3D objects using a monocular RGB camera. The key idea is to derive a region-based cost function using temporally c…