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dc.contributor.authorSalvador Aguilera, Amaia
dc.contributor.authorDrozdzal, Michal
dc.contributor.authorGiró Nieto, Xavier
dc.contributor.authorRomero, Adriana
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Teoria del Senyal i Comunicacions
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2019-07-26T09:31:22Z
dc.date.available2019-07-26T09:31:22Z
dc.date.issued2019
dc.identifier.citationSalvador, A. [et al.]. Inverse cooking: recipe generation from food images. A: IEEE Conference on Computer Vision and Pattern Recognition. "CVPR 2019: Conference on Computer Vision and Pattern Recognition: Long Beach, CA: June 16-20, 2019". Computer Vision Foundation, 2019, p. 10453-10462.
dc.identifier.urihttp://hdl.handle.net/2117/166916
dc.description.abstractPeople enjoy food photography because they appreciate food. Behind each meal there is a story described in a complex recipe and, unfortunately, by simply looking at a food image we do not have access to its preparation process. Therefore, in this paper we introduce an inverse cooking system that recreates cooking recipes given food images. Our system predicts ingredients as sets by means of a novel architecture, modeling their dependencies without imposing any order, and then generates cooking instructions by attending to both image and its inferred ingredients simultaneously. We extensively evaluate the whole system on the large-scale Recipe1M dataset and show that (1) we improve performance w.r.t. previous baselines for ingredient prediction; (2) we are able to obtain high quality recipes by leveraging both image and ingredients; (3) our system is able to produce more compelling recipes than retrieval-based approaches according to human judgment. We make code and models publicly available.
dc.format.extent10 p.
dc.language.isoeng
dc.publisherComputer Vision Foundation
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes
dc.subject.lcshComputer vision
dc.subject.lcshPattern recognition systems
dc.subject.otherCooking
dc.subject.otherRecipe
dc.subject.otherGenerative models
dc.subject.otherim2recipe
dc.titleInverse cooking: recipe generation from food images
dc.typeConference report
dc.subject.lemacReconeixement de formes (Informàtica)
dc.subject.lemacVisió per ordinador
dc.contributor.groupUniversitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://openaccess.thecvf.com/content_CVPR_2019/html/Salvador_Inverse_Cooking_Recipe_Generation_From_Food_Images_CVPR_2019_paper.html
dc.rights.accessOpen Access
local.identifier.drac25441675
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TEC2013-43935-R
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TEC2016-75976-R
local.citation.authorSalvador, A.; Drozdzal, M.; Giro, X.; Romeroa, A.
local.citation.contributorIEEE Conference on Computer Vision and Pattern Recognition
local.citation.publicationNameCVPR 2019: Conference on Computer Vision and Pattern Recognition: Long Beach, CA: June 16-20, 2019
local.citation.startingPage10453
local.citation.endingPage10462


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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain