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Titel:

TUMTraf Intersection Dataset: All You Need for Urban 3D Camera-LiDAR Roadside Perception [Best Student Paper Award]

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Zimmer, Walter; Creß, Christian; Nguyen, Huu Tung; Knoll, Alois C.
Seitenangaben Beitrag:
1030-1037
Abstract:
Intelligent Transportation Systems (ITS) allow a drastic expansion of the visibility range and decrease occlusions for autonomous driving. To obtain accurate detections, detailed labeled sensor data for training is required. Unfortunately, high-quality 3D labels of LiDAR point clouds from the infrastructure perspective of an intersection are still rare. Therefore, we provide the TUM Traffic (TUMTraf) Intersection Dataset, which consists of labeled LiDAR point clouds and synchronized camera image...     »
Stichworte:
Dataset, 3D Perception, Camera, LiDAR, Intelligent Transportation Systems, Autonomous Driving
Dewey-Dezimalklassifikation:
000 Informatik, Wissen, Systeme
Herausgeber:
IEEE
Kongress- / Buchtitel:
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Datum der Konferenz:
24-28 September 2023
Verlag / Institution:
IEEE
Publikationsdatum:
13.02.2024
Jahr:
2024
Quartal:
1. Quartal
Jahr / Monat:
2024-02
Monat:
Feb
Seiten:
8
Print-ISBN:
979-8-3503-9947-9
E-ISBN:
979-8-3503-9946-2
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1109/ITSC57777.2023.10422289
WWW:
https://ieeexplore.ieee.org/document/10422289
TUM Einrichtung:
Chair of Robotics, Artificial Intelligence and Real-time Systems
Copyright Informationen:
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.
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