activity
20172021
most citedLearning to Reconstruct People in Clothing from a Single RGB Camera

13 citations · 23 across the 4 of their papers we have counts for

collaborators

8 papers

cs.CV2021

Sampling Based Scene-Space Video Processing

Felix Klose, Oliver Wang, Jean-Charles Bazin +2

Many compelling video processing effects can be achieved if per-pixel depth information and 3D camera calibrations are known. However, the success of such methods is highly depende…

cs.CV2020

High-Fidelity Neural Human Motion Transfer from Monocular Video

Moritz Kappel, Vladislav Golyanik, Mohamed Elgharib +5

Video-based human motion transfer creates video animations of humans following a source motion. Current methods show remarkable results for tightly-clad subjects. However, the lack…

cs.CV201913 cited

Learning to Reconstruct People in Clothing from a Single RGB Camera

Thiemo Alldieck, Marcus Magnor, Bharat Lal Bhatnagar +2

We present 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, in less than 10 seconds w…

cs.CV2019

Tex2Shape: Detailed Full Human Body Geometry From a Single Image

Thiemo Alldieck, Gerard Pons-Moll, Christian Theobalt +1

We present a simple yet effective method to infer detailed full human body shape from only a single photograph. Our model can infer full-body shape including face, hair, and clothi…

physics.ed-ph201910 cited

Augmenting the fine beam tube: From hybrid measurements to magnetic field visualization

Oliver Bodensiek, Doerte Sonntag, Nils Wendorff +2

We present an Augmented Reality (AR) enhanced and networked fine beam tube experiment for undergraduate physics education. In order to determine the charge-to-mass ratio of the ele…

cs.CV2018

Detailed Human Avatars from Monocular Video

Thiemo Alldieck, Marcus Magnor, Weipeng Xu +2

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 resemble subjects…