Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/117925
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dc.contributor.authorPeñate Sánchez, Adriánen_US
dc.contributor.authorAgapito, Lourdesen_US
dc.date.accessioned2022-09-07T15:27:17Z-
dc.date.available2022-09-07T15:27:17Z-
dc.date.issued2019en_US
dc.identifier.isbn978-3-030-20886-8en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10553/117925-
dc.description.abstractWe present 3D Pick & Mix, a new 3D shape retrieval system that provides users with a new level of freedom to explore 3D shape and Internet image collections by introducing the ability to reason about objects at the level of their constituent parts. While classic retrieval systems can only formulate simple searches such as “find the 3D model that is most similar to the input image” our new approach can formulate advanced and semantically meaningful search queries such as: “find me the 3D model that best combines the design of the legs of the chair in image 1 but with no armrests, like the chair in image 2”. Many applications could benefit from such rich queries, users could browse through catalogues of furniture and pick and mix parts, combining for example the legs of a chair from one shop and the armrests from another shop.en_US
dc.languageengen_US
dc.publisherSpringeren_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceJawahar, C., Li, H., Mori, G., Schindler, K. (eds) Computer Vision – ACCV 2018. Lecture Notes in Computer Science, vol 11361, pp 155–170 (2018). Springer, Cham.en_US
dc.subject1203 Ciencia de los ordenadoresen_US
dc.subject.otherShape blendingen_US
dc.subject.otherImage embeddingen_US
dc.subject.otherShape retrievalen_US
dc.title3D pick & mix: object part blending in joint shape and image manifoldsen_US
dc.typeConference Paperen_US
dc.relation.conferenceAsian Conference in Computer Vision (ACCV)en_US
dc.identifier.doi10.1007/978-3-030-20887-5_10en_US
dc.identifier.scopus2-s2.0-85066800002-
dc.identifier.isiWOS:000492901400010-
dc.contributor.orcid0000-0003-2876-3301-
dc.description.lastpage170en_US
dc.description.firstpage155en_US
dc.relation.volume11361en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.identifier.external67238896-
dc.description.numberofpages16en_US
dc.identifier.eisbn978-3-030-20887-5-
dc.utils.revisionen_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INFen_US
dc.description.sjr0,427
dc.description.sjrqQ2
item.grantfulltextrestricted-
item.fulltextCon texto completo-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Redes Neuronales, Aprendizaje Automático e Ingeniería de Datos-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0003-2876-3301-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNamePeñate Sánchez, Adrián-
Colección:Actas de congresos
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