Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/55091
Campo DC Valoridioma
dc.contributor.authorMarin-Reyes, Pedro Antonioen_US
dc.contributor.authorBergamini, Lucaen_US
dc.contributor.authorLorenzo-Navarro, Javieren_US
dc.contributor.authorPalazzi, Andreaen_US
dc.contributor.authorCalderara, Simoneen_US
dc.contributor.authorCucchiara, Ritaen_US
dc.date.accessioned2019-02-18T16:28:40Z-
dc.date.available2019-02-18T16:28:40Z-
dc.date.issued2018en_US
dc.identifier.isbn9781538661000en_US
dc.identifier.issn2160-7508en_US
dc.identifier.urihttp://hdl.handle.net/10553/55091-
dc.description.abstractVehicle re-identification plays a major role in modern smart surveillance systems. Specifically, the task requires the capability to predict the identity of a given vehicle, given a dataset of known associations, collected from different views and surveillance cameras. Generally, it can be cast as a ranking problem: given a probe image of a vehicle, the model needs to rank all database images based on their similarities w.r.t the probe image. In line with recent research, we devise a metric learning model that employs a supervision based on local constraints. In particular, we leverage pairwise and triplet constraints for training a network capable of assigning a high degree of similarity to samples sharing the same identity, while keeping different identities distant in feature space. Eventually, we show how vehicle tracking can be exploited to automatically generate a weakly labelled dataset that can be used to train the deep network for the task of vehicle re-identification. Learning and evaluation is carried out on the NVIDIA AI city challenge videos.
dc.languagespaen_US
dc.publisher2160-7508en_US
dc.relation.ispartofIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshopsen_US
dc.sourceIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops[ISSN 2160-7508],v. 2018-June (8575466), p. 166-171en_US
dc.subject120304 Inteligencia artificialen_US
dc.titleUnsupervised vehicle re-identification using triplet networksen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conferenceIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
dc.relation.conference31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018
dc.identifier.doi10.1109/CVPRW.2018.00030
dc.identifier.scopus85060889621
dc.identifier.isi000457636800023
dc.contributor.authorscopusid57191274555
dc.contributor.authorscopusid15924875500
dc.contributor.authorscopusid15042453800
dc.contributor.authorscopusid57191537487
dc.contributor.authorscopusid23099524400
dc.contributor.authorscopusid7006870483
dc.description.lastpage171-
dc.identifier.issue8575466-
dc.description.firstpage166-
dc.relation.volume2018-June-
dc.type2Actas de congresosen_US
dc.contributor.daisngid15775956
dc.contributor.daisngid12286502
dc.contributor.daisngid3855775
dc.contributor.daisngid1062730
dc.contributor.daisngid2489695
dc.contributor.daisngid93064
dc.contributor.wosstandardWOS:Marin-Reyes, PA
dc.contributor.wosstandardWOS:Palazzi, A
dc.contributor.wosstandardWOS:Bergamini, L
dc.contributor.wosstandardWOS:Calderara, S
dc.contributor.wosstandardWOS:Lorenzo-Navarro, J
dc.contributor.wosstandardWOS:Cucchiara, R
dc.date.coverdate2018
dc.identifier.conferenceidevents121134
dc.identifier.ulpgces
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.event.eventsstartdate18-06-2018-
crisitem.event.eventsstartdate18-06-2018-
crisitem.event.eventsenddate22-06-2018-
crisitem.event.eventsenddate22-06-2018-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Robótica y Oceanografía Computacional-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Robótica y Oceanografía Computacional-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0002-2834-2067-
crisitem.author.orcid0000-0002-2834-2067-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameLorenzo Navarro, José Javier-
crisitem.author.fullNameLorenzo Navarro, José Javier-
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