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Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
27.05.2021
Verantwortlich:
Kuhn, Christopher
Autorinnen / Autoren:
Kuhn, Christopher ; Hofbauer, Markus : Xu, Murong ; Steinbach, Eckehard
Institutionszugehörigkeit:
TUM
Herausgeber:
TUM
Titel:
Densely Annotated Video Driving Data Set
Enddatum der Datenerzeugung:
09.04.2020
Fachgebiet:
DAT Datenverarbeitung, Informatik
zusätzliche Fachgebiete:
Semantic segmentation of video sequences
Quellen der Daten:
Simulationen / simulations
Datentyp:
Bilder / images; Video-Aufzeichnungen / audiovisual collection
Anderer Datentyp:
Videos plus semantic labels
Methode der Datenerhebung:
The CARLA simulator was used to record rosbags of driving data from which the images and ground-truth semantic labels were extracted.
Beschreibung:
This data set consists of 28 video sequences of driving recorded in the CARLA simulator, resulting in a total of 10767 frames. For each frame, pixel-wise semantic labels are provided. The scenes are recorded in dynamic weather and traffic conditions.
Links:

Article: https://mediatum.ub.tum.de/node?id=1612342& change_language=en

Schlagworte:
Computer Vision; Semantic Segmentation; Autonomous Driving; Video Processing
Technische Hinweise:
View and download (5.87 GB total, 2.1536 files)
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The data server also offers downloads with rsync (password m1596437):
rsync rsync://m1596437@dataserv.ub.tum.de/m1596437/
Sprache:
en
Rechte:
by, http://creativecommons.org/licenses/by/4.0
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