Zobrazeno 1 - 10
of 174
pro vyhledávání: '"Peter Eisert"'
Autor:
Yonghao Chen, Tilman Stephani, Milena Teresa Bagdasarian, Anna Hilsmann, Peter Eisert, Arno Villringer, Sebastian Bosse, Michael Gaebler, Vadim V. Nikulin
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Artificially created human faces play an increasingly important role in our digital world. However, the so-called uncanny valley effect may cause people to perceive highly, yet not perfectly human-like faces as eerie, bringing challenges to
Externí odkaz:
https://doaj.org/article/764592db42944436984f03113e917af8
Publikováno v:
Graphical Models, Vol 129, Iss , Pp 101199- (2023)
This paper presents a novel approach for text/speech-driven animation of a photo-realistic head model based on blend-shape geometry, dynamic textures, and neural rendering. Training a VAE for geometry and texture yields a parametric model for accurat
Externí odkaz:
https://doaj.org/article/01ebd96c452f4afe9cf70af6d98b1900
Autor:
Sebastian P. Schraven, Benjamin Kossack, Daniel Strüder, Maximillian Jung, Lotte Skopnik, Justus Gross, Anna Hilsmann, Peter Eisert, Robert Mlynski, Eric L. Wisotzky
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Abstract Flap loss through limited perfusion remains a major complication in reconstructive surgery. Continuous monitoring of perfusion will facilitate early detection of insufficient perfusion. Remote or imaging photoplethysmography (rPPG/iPPG) as a
Externí odkaz:
https://doaj.org/article/d36d012f13484807a78d7c3abcc6e680
Publikováno v:
Computational Visual Media, Vol 9, Iss 1, Pp 123-139 (2022)
Abstract Accurate and temporally consistent modeling of human bodies is essential for a wide range of applications, including character animation, understanding human social behavior, and AR/VR interfaces. Capturing human motion accurately from a mon
Externí odkaz:
https://doaj.org/article/99ea035db5274107894e1de71288d3de
Publikováno v:
Sensors, Vol 23, Iss 13, p 6138 (2023)
We investigate an edge-computing scenario for robot control, where two similar neural networks are running on one computational node. We test the feasibility of using a single object-detection model (YOLOv5) with the benefit of reduced computational
Externí odkaz:
https://doaj.org/article/471be74226a2486f84faf8b61c356d76
Autor:
Paul Chojecki, Dominykas Strazdas, David Przewozny, Niklas Gard, Detlef Runde, Niklas Hoerner, Ayoub Al-Hamadi, Peter Eisert, Sebastian Bosse
Publikováno v:
Sensors, Vol 23, Iss 11, p 5043 (2023)
Multimodal user interfaces promise natural and intuitive human–machine interactions. However, is the extra effort for the development of a complex multisensor system justified, or can users also be satisfied with only one input modality? This study
Externí odkaz:
https://doaj.org/article/81fc137f82d04e9ea1d7b0adf964cc25
Autor:
Anna Hilsmann, Philipp Fechteler, Wieland Morgenstern, Wolfgang Paier, Ingo Feldmann, Oliver Schreer, Peter Eisert
Publikováno v:
IET Computer Vision, Vol 14, Iss 6, Pp 350-358 (2020)
An end‐to‐end pipeline for the creation of high‐quality animatable volumetric video of human performances is presented. Going beyond the application of free‐viewpoint video, the authors allow re‐animation and alteration of an actor's perfor
Externí odkaz:
https://doaj.org/article/9fe1f76e86514b8985ff7d38bfbbc96d
Publikováno v:
IET Computer Vision, Vol 14, Iss 6, Pp 359-369 (2020)
Creating realistic animations of human faces is still a challenging task in computer graphics. While computer graphics (CG) models capture much variability in a small parameter vector, they usually do not meet the necessary visual quality. This is du
Externí odkaz:
https://doaj.org/article/f19d26ba9c1446df858c69b340f33a95
Publikováno v:
Computers, Vol 10, Iss 9, p 117 (2021)
Detecting morphed face images has become an important task to maintain the trust in automated verification systems based on facial images, e.g., at automated border control gates. Deep Neural Network (DNN)-based detectors have shown remarkable result
Externí odkaz:
https://doaj.org/article/01188efbed604ed7b6026e7e561278c9
Autor:
Maria Teresa Linaza, Jorge Posada, Jürgen Bund, Peter Eisert, Marco Quartulli, Jürgen Döllner, Alain Pagani, Igor G. Olaizola, Andre Barriguinha, Theocharis Moysiadis, Laurent Lucat
Publikováno v:
Agronomy, Vol 11, Iss 6, p 1227 (2021)
One of the main challenges for the implementation of artificial intelligence (AI) in agriculture includes the low replicability and the corresponding difficulty in systematic data gathering, as no two fields are exactly alike. Therefore, the comparis
Externí odkaz:
https://doaj.org/article/eac071940c964e14890490ad219cfb3f