Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Janis Sprenger"'
Publikováno v:
2021 IEEE Intelligent Vehicles Symposium (IV).
The prediction of pedestrian behavior remains a major objective for the development of autonomous vehicles. Pedestrians do not merely represent the most vulnerable traffic participants, but are also a challenge in the prediction process, since their
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2c37ca9ce9d266415360b2c489e694a
https://doi.org/10.1109/iv48863.2021.9575809
https://doi.org/10.1109/iv48863.2021.9575809
Publikováno v:
MIG
The simulation of humanoid avatars is relevant for a multitude of applications, such as movies, games, simulations for autonomous vehicles, virtual avatars and many more. In order to achieve the simulation of realistic and believable characters, it i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60479685857eaa621f60d8788ea3b20e
https://doi.org/10.1145/3359566.3360082
https://doi.org/10.1145/3359566.3360082
Publikováno v:
MIG
Motion synthesis approaches are widely used throughout different domains such as gaming, virtual crowds or simulation within production industries. With ongoing digitization, these systems are becoming increasingly indispensable. In general, the util
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1f57fbb68bd1de85e37a494d9398824
https://doi.org/10.1145/3359566.3360052
https://doi.org/10.1145/3359566.3360052
Publikováno v:
MIG
We propose a novel approach to create generative models for distinctive styles of locomotion for humanoid characters. Our approach only requires a single or a few style examples and a neutral motion database. We are inspired by the observation that h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2eeaf4ce686d4f530b0b9632c8804bab
https://doi.org/10.1145/3359566.3360083
https://doi.org/10.1145/3359566.3360083
Autor:
Patrick Trampert, Faysal Boughorbel, Christian Kübel, Tim Dahmen, Matthias Klusch, Philipp Slusallek, Janis Sprenger, Klaus Fischer
Publikováno v:
AI Perspectives. 1
Hierarchical neural networks with large numbers of layers are the state of the art for most computer vision problems including image classification, multi-object detection and semantic segmentation. While the computational demands of training such de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78c3dc548de544827a9dd784e6b105bd
https://doi.org/10.1186/s42467-019-0002-0
https://doi.org/10.1186/s42467-019-0002-0
Publikováno v:
CASA
The pedestrian intention is not only signalized by their past trajectory and head gaze direction, but by their whole body movement. In order to improve existing algorithms, analysis of pedestrian motions before entering a shared environment, like a s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3845356ad6420b17cac0989c03a90df4
https://doi.org/10.1145/3328756.3328776
https://doi.org/10.1145/3328756.3328776
Autor:
Janis Sprenger, Han Du, Erik Herrmann, Somayeh Hosseini, Noshaba Cheema, Klaus Fischer, Philipp Slusallek
Publikováno v:
I3D
To enable the physically correct simulation of the interaction of a 3D character with its environment the internal joint forces of a physical model of the character need to be estimated. Recently, derivative-free sampling-based optimization methods,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::825009f6b5b4d1749a9c3a5b6ff21129
https://doi.org/10.1145/3306131.3317027
https://doi.org/10.1145/3306131.3317027
Autor:
André Antakli, Dmitri Rubinstein, Torsten Spieldenner, Ingo Zinnikus, Janis Sprenger, Daniel Spieldenner, Erik Herrmann
Publikováno v:
WEBIST
In the production industry, in recent years more and more hybrid teams of workers and robots are being used to improve flexible processes. The production environment of the future will include hybrid teams in which workers cooperate more tightly toge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d36139fe5400858347713e9c91d8d2f
https://doi.org/10.5220/0008163000880099
https://doi.org/10.5220/0008163000880099
Publikováno v:
SEFAIAS@ICSE
In order to make highly/fully automated driving safe, synthetic training and validation data will be required, because critical road situations are too divers and too rare. A few studies on using synthetic data have been published, reporting a genera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff55cf3bb181fb9aacb878e277759eef
https://doi.org/10.1145/3194085.3194093
https://doi.org/10.1145/3194085.3194093
Publikováno v:
SEFAIAS@ICSE
In this paper, we investigate the link between machine perception and human perception for highly/fully automated driving. We compare the classification results of a camera-based frame-by-frame semantic segmentation model (Machine) with a well-establ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03de9885d457d3187a6dce67b5e10018
https://doi.org/10.1145/3194085.3194092
https://doi.org/10.1145/3194085.3194092