All for one, and one for all: UrbanSyn Dataset, the third Musketeer of synthetic driving scenes

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UDC.coleccionInvestigaciónes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.grupoInvComputer Graphics & Visual Computing (XLab)es_ES
UDC.institutoCentroCITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicaciónes_ES
UDC.journalTitleNeurocomputinges_ES
UDC.startPage130038es_ES
UDC.volume637es_ES
dc.contributor.authorGómez Zurita, José Luis
dc.contributor.authorSilva, Manuel
dc.contributor.authorSeoane, Antonio
dc.contributor.authorBorràs, Agnés
dc.contributor.authorNoriega, M. A.
dc.contributor.authorRos, German
dc.contributor.authorIglesias-Guitian, Jose A.
dc.contributor.authorLópez, Antonio M.
dc.date.accessioned2025-05-14T12:08:21Z
dc.date.embargoEndDate2027-03-07es_ES
dc.date.embargoLift2027-03-07
dc.date.issued2025-03-25
dc.descriptionThis manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/. This version of the article has been accepted for publication in Neurocomputing (ISSN 1872-8286).es_ES
dc.description.abstract[Abstract]: We introduce UrbanSyn, a photorealistic dataset acquired through semi-procedurally generated synthetic urban driving scenarios. Developed using high-quality geometry and materials, UrbanSyn provides pixel-level ground truth, including depth, semantic segmentation, and instance segmentation with object bounding boxes and occlusion degree. It complements GTAV and Synscapes datasets to form what we coin as the 'Three Musketeers'. We demonstrate the value of the Three Musketeers in unsupervised domain adaptation for image semantic segmentation. Results on real-world datasets, Cityscapes, Mapillary Vistas, and BDD100K, establish new benchmarks, largely attributed to UrbanSyn. We make UrbanSyn openly and freely accessiblees_ES
dc.description.sponsorshipThis work has been supported by the Spanish grants Ref. PID2020-115734RB-C21 (ADA/SSL-ADA subproject) and PID2020-115734RB-C22 (ADA/PGAS-ADA subproject), both funded by MCIN/AEI/ 10.13039/501100011033. Antonio M. López acknowledges the financial support to his general research activities given by ICREA under the ICREA Academia Program, Spain. CVC’s authors acknowledge the support of the Generalitat de Catalunya CERCA Program and its ACCIO agency to CVC’s general activities. Jose A. Iglesias-Guitian acknowledges the financial support to his general research activities given by UDC-Inditex InTalent programme, the Spanish Ministry of Science and Innovation (AEI/RYC2018-025385-I), and Xunta de Galicia, Spain (ED431F 2021/11, EU-FEDER ED431G 2019/01)es_ES
dc.description.sponsorshipXunta de Galicia; ED431F 2021/11es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.identifier.citationGómez, J. L., Silva, M., Seoane, A. M., Borràs, A., Noriega, M., Ros, G., Iglesias-Guitian, J. A., & López, A. M. (2025). All for one, and one for all: UrbanSyn Dataset, the third Musketeer of synthetic driving scenes. Neurocomputing, 637, 130038. https://doi.org/10.1016/j.neucom.2025.130038es_ES
dc.identifier.issn0925-2312
dc.identifier.issn1872-8286
dc.identifier.urihttp://hdl.handle.net/2183/41990
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-115734RB-C21/ES/APRENDIZAJE SEMI-SUPERVISADO PARA LA ANOTACION AUTOMATICA DE DATOSes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-115734RB-C22/ES/GENERACIÓN PROCEDURAL DE ESCENARIOS AUMENTADOS CON ANOTACIÓN DE DATOS AUTOMÁTICAes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RYC2018-025385-I/ES/es_ES
dc.relation.urihttps://doi.org/10.1016/j.neucom.2025.130038es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Españaes_ES
dc.rights© 2025 Elsevier B.V.es_ES
dc.rights.accessRightsembargoed accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectAutonomous drivinges_ES
dc.subjectSynthetic dataes_ES
dc.subjectDomain adaptationes_ES
dc.subjectSemantic segmentationes_ES
dc.titleAll for one, and one for all: UrbanSyn Dataset, the third Musketeer of synthetic driving sceneses_ES
dc.typejournal articlees_ES
dc.type.hasVersionAMes_ES
dspace.entity.typePublication
relation.isAuthorOfPublicationffea890b-c75c-45b4-bf91-0566130b3b08
relation.isAuthorOfPublication2baabfcd-ac55-477b-a5db-4f31be84703f
relation.isAuthorOfPublication.latestForDiscoveryffea890b-c75c-45b4-bf91-0566130b3b08

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