6 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.CV2020★ 2 cited
CALVIS: chest, waist and pelvis circumference from 3D human body meshes as ground truth for deep learning
Yansel Gonzalez Tejeda, Helmut Mayer
In this paper we present CALVIS, a method to calculate hest, wist and pe circumference from 3D human body meshes. Our motivation is to use th…
cs.CV2019★ 6 cited
RPBA -- Robust Parallel Bundle Adjustment Based on Covariance Information
Helmut Mayer
A core component of all Structure from Motion (SfM) approaches is bundle adjustment. As the latter is a computational bottleneck for larger blocks, parallel bundle adjustment has b…
cs.CV2019★ 1 cited
Adding Intuitive Physics to Neural-Symbolic Capsules Using Interaction Networks
Michael Kissner, Helmut Mayer
Many current methods to learn intuitive physics are based on interaction networks and similar approaches. However, they rely on information that has proven difficult to estimate di…