ARC Synthetic Riverine Waste
dc.contributor.author
Kolvenbach, Hendrik
dc.contributor.author
Strübin, Dario
dc.contributor.author
Stolle, Jonas
dc.contributor.author
Voellmy, Xenia
dc.contributor.author
Esquivel Estay, Fidel
dc.date.accessioned
2024-10-09T10:47:42Z
dc.date.available
2024-09-13T14:26:25Z
dc.date.available
2024-09-16T12:59:26Z
dc.date.available
2024-09-27T09:10:03Z
dc.date.available
2024-09-27T13:10:35Z
dc.date.available
2024-10-09T10:47:42Z
dc.date.issued
2024-09-27
dc.identifier.uri
http://hdl.handle.net/20.500.11850/693904
dc.identifier.doi
10.3929/ethz-b-000693904
dc.description.abstract
The Autonomous River Cleanup (ARC), led by students at the Robotic Systems Lab, aims to tackle waste pollution in rivers using robotics and machine learning. The team consists mainly of volunteers and students, with guidance from experienced researchers, and focuses on waste analysis and sorting.
This dataset results from a synthetic waste generation pipeline developed by Xenia Voellmy and Dario Strübin as part of their Master's thesis at ARC. Real waste items were digitized in 3D, then deformed and textured using Blender to simulate the variations commonly found in riverine waste.
A set of RGB images, depth images, and segmentation masks are provided containing multiple synthetic waste items on randomized backgrounds with item-wise annotations in the coco format.
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application/zip
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dc.format
text/csv
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text/plain
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dc.format
application/json
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dc.format
image/png
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dc.language.iso
en
en_US
dc.publisher
ETH Zurich
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-sa/4.0/
dc.title
ARC Synthetic Riverine Waste
en_US
dc.type
Dataset
dc.rights.license
Creative Commons Attribution-ShareAlike 4.0 International
ethz.size
19.18 GB
en_US
ethz.publication.place
Zurich
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::09570 - Hutter, Marco / Hutter, Marco
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::09570 - Hutter, Marco / Hutter, Marco
en_US
ethz.date.retentionend
indefinite
en_US
ethz.date.retentionendDate
n/a
ethz.date.deposited
2024-09-13T14:26:25Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2024-09-27T13:17:12Z
ethz.rosetta.lastUpdated
2024-09-27T13:17:12Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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