Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Daniel Steininger"'
Autor:
Phillipp Fanta-Jende, Daniel Steininger, Alexander Kern, Verena Widhalm, Javier G. Apud Baca, Markus Hofstätter, Julia Simon, Felix Bruckmüller, Christoph Sulzbachner
Publikováno v:
PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science.
Whilst mapping with UAVs has become an established tool for geodata acquisition in many domains, certain time-critical applications, such as crisis and disaster response, demand fast geodata processing pipelines rather than photogrammetric post-proce
Autor:
Daniel Steininger, Andreas Kriegler, Wolfgang Pointner, Verena Widhalm, Julia Simon, Oliver Zendel
Publikováno v:
Computer Vision – ACCV 2022 Workshops ISBN: 9783031270659
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15a9704c42d42783037f2e8f7179ab11
https://doi.org/10.1007/978-3-031-27066-6_11
https://doi.org/10.1007/978-3-031-27066-6_11
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Publikováno v:
Pattern Recognition and Image Analysis ISBN: 9783031048807
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e4edf6b66374641df8fa72d1fc1a83f
https://doi.org/10.1007/978-3-031-04881-4_34
https://doi.org/10.1007/978-3-031-04881-4_34
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B1-2020, Pp 429-435 (2020)
In recent years, the proliferation and further development of unmanned aerial vehicles (UAVs) led to a great number of key technologies, advances and opportunities especially in the realm of time-critical applications. UAVs as a platform provide a un
Publikováno v:
Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030687861
ICPR Workshops (7)
ICPR Workshops (7)
Automated monitoring and analysis of passenger movement in safety-critical parts of transport infrastructures represent a relevant visual surveillance task. Recent breakthroughs in visual representation learning and spatial sensing opened up new poss
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6aea35f697a1b961bc016227b6959632
https://doi.org/10.1007/978-3-030-68787-8_47
https://doi.org/10.1007/978-3-030-68787-8_47
Publikováno v:
ICCV Workshops
In this paper, we tackle the challenge for VSLAM of handling non-static environments. We propose to include semantic information obtained by deep learning methods in the traditional geometric pipeline. Specifically, we compute a confidence measure fo
Publikováno v:
Cognitive Internet of Things: Frameworks, Tools and Applications ISBN: 9783030049454
Human detection in crowded situations represents a challenging task in many practically relevant scenarios. In this paper we propose a passive stereo depth based human detection scheme employing a hierarchically-structured tree of learned shape templ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7264b8c59df14027f8b85c194c013e4a
https://doi.org/10.1007/978-3-030-04946-1_47
https://doi.org/10.1007/978-3-030-04946-1_47
Publikováno v:
2018 10th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS).
Recognizing humans from aerial views represents an increasingly relevant endeavor; a trend mainly driven by the widespread use of unmanned aerial vehicles (UAVs). An accurate and real-time visual human recognition task, however, represents a scientif
Autor:
Gustavo Fernández Domínguez, Daniel Steininger, Markus Murschitz, Katrin Honauer, Oliver Zendel
Publikováno v:
Computer Vision – ECCV 2018-15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part VI
Computer Vision – ECCV 2018 ISBN: 9783030012304
ECCV (6)
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Vision – ECCV 2018
Computer Vision – ECCV 2018 ISBN: 9783030012304
ECCV (6)
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Vision – ECCV 2018
Test datasets should contain many different challenging aspects so that the robustness and real-world applicability of algorithms can be assessed. In this work, we present a new test dataset for semantic and instance segmentation for the automotive d