; ; ; ;
2025
Online
URL: https://github.com/ika-rwth-aachen/OCCUQ
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Dokumenttyp
Conference Presentation
Format
online
Sprache
English
Interne Identnummern
RWTH-2025-05330
Datensatz-ID: 1013087
Preprint
OCCUQ: Exploring Efficient Uncertainty Quantification for 3D Occupancy Prediction
IEEE International Conference on Robotics & Automation, ICRA, AtlantaAtlanta, USA, 19 May 2025 - 23 May 2025
9 Seiten (2025) [10.48550/arXiv.2503.10605]
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Poster
OCCUQ: Exploring Efficient Uncertainty Quantification for 3D Occupancy Prediction
IEEE International Conference on Robotics & Automation, AtlantaAtlanta, USA,
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Contribution to a book/Contribution to a conference proceedings
OCCUQ: Exploring Efficient Uncertainty Quantification for 3D Occupancy Prediction
2025 IEEE International Conference on Robotics and Automation : May 19-23, 2025, Atlanta, GA, USA / IEEE Robotics & Automation Society, IEEE ; ICRA - IEEE International Conference on Robotics and Automation ; general chairs: Seth Hutchinson (Northeastern University), Nancy Amato (University of Illinois at Urbana-Champaign) ; publications committee - chair: Todd Murphey (Northwestern University)/co-chairs: Zhidong Wang (Chiba Institute of Technology)
IEEE International Conference on Robotics & Automation, ICRA 2025, Atlanta, GAAtlanta, GA, USA, 19 May 2025 - 23 May 2025
[Piscataway, NJ] : IEEE 4884-4891 (2025) [10.1109/ICRA55743.2025.11128049]
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