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Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition

Every year, the VISion Understanding and Machine intelligence (VISUM) summer school runs a competition where participants can learn and share knowledge about Computer Vision and Machine Learning in a vibrant environment. 2021 VISUM’s focused on applying those methodologies in fashion. Recently, ther...

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Autores principales: Castro, Eduardo, Ferreira, Pedro M., Rebelo, Ana, Rio-Torto, Isabel, Capozzi, Leonardo, Ferreira, Mafalda Falcão, Gonçalves, Tiago, Albuquerque, Tomé, Silva, Wilson, Afonso, Carolina, Gamelas Sousa, Ricardo, Cimarelli, Claudio, Daoudi, Nadia, Moreira, Gabriel, Yang, Hsiu-yu, Hrga, Ingrid, Ahmad, Javed, Keswani, Monish, Beco, Sofia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801353/
https://www.ncbi.nlm.nih.gov/pubmed/36597466
http://dx.doi.org/10.1007/s00138-022-01359-x
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author Castro, Eduardo
Ferreira, Pedro M.
Rebelo, Ana
Rio-Torto, Isabel
Capozzi, Leonardo
Ferreira, Mafalda Falcão
Gonçalves, Tiago
Albuquerque, Tomé
Silva, Wilson
Afonso, Carolina
Gamelas Sousa, Ricardo
Cimarelli, Claudio
Daoudi, Nadia
Moreira, Gabriel
Yang, Hsiu-yu
Hrga, Ingrid
Ahmad, Javed
Keswani, Monish
Beco, Sofia
author_facet Castro, Eduardo
Ferreira, Pedro M.
Rebelo, Ana
Rio-Torto, Isabel
Capozzi, Leonardo
Ferreira, Mafalda Falcão
Gonçalves, Tiago
Albuquerque, Tomé
Silva, Wilson
Afonso, Carolina
Gamelas Sousa, Ricardo
Cimarelli, Claudio
Daoudi, Nadia
Moreira, Gabriel
Yang, Hsiu-yu
Hrga, Ingrid
Ahmad, Javed
Keswani, Monish
Beco, Sofia
author_sort Castro, Eduardo
collection PubMed
description Every year, the VISion Understanding and Machine intelligence (VISUM) summer school runs a competition where participants can learn and share knowledge about Computer Vision and Machine Learning in a vibrant environment. 2021 VISUM’s focused on applying those methodologies in fashion. Recently, there has been an increase of interest within the scientific community in applying computer vision methodologies to the fashion domain. That is highly motivated by fashion being one of the world’s largest industries presenting a rapid development in e-commerce mainly since the COVID-19 pandemic. Computer Vision for Fashion enables a wide range of innovations, from personalized recommendations to outfit matching. The competition enabled students to apply the knowledge acquired in the summer school to a real-world problem. The ambition was to foster research and development in fashion outfit complementary product retrieval by leveraging vast visual and textual data with domain knowledge. For this, a new fashion outfit dataset (acquired and curated by FARFETCH) for research and benchmark purposes is introduced. Additionally, a competitive baseline with an original negative sampling process for triplet mining was implemented and served as a starting point for participants. The top 3 performing methods are described in this paper since they constitute the reference state-of-the-art for this particular problem. To our knowledge, this is the first challenge in fashion outfit complementary product retrieval. Moreover, this joint project between academia and industry brings several relevant contributions to disseminating science and technology, promoting economic and social development, and helping to connect early-career researchers to real-world industry challenges.
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spelling pubmed-98013532022-12-30 Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition Castro, Eduardo Ferreira, Pedro M. Rebelo, Ana Rio-Torto, Isabel Capozzi, Leonardo Ferreira, Mafalda Falcão Gonçalves, Tiago Albuquerque, Tomé Silva, Wilson Afonso, Carolina Gamelas Sousa, Ricardo Cimarelli, Claudio Daoudi, Nadia Moreira, Gabriel Yang, Hsiu-yu Hrga, Ingrid Ahmad, Javed Keswani, Monish Beco, Sofia Mach Vis Appl Original Paper Every year, the VISion Understanding and Machine intelligence (VISUM) summer school runs a competition where participants can learn and share knowledge about Computer Vision and Machine Learning in a vibrant environment. 2021 VISUM’s focused on applying those methodologies in fashion. Recently, there has been an increase of interest within the scientific community in applying computer vision methodologies to the fashion domain. That is highly motivated by fashion being one of the world’s largest industries presenting a rapid development in e-commerce mainly since the COVID-19 pandemic. Computer Vision for Fashion enables a wide range of innovations, from personalized recommendations to outfit matching. The competition enabled students to apply the knowledge acquired in the summer school to a real-world problem. The ambition was to foster research and development in fashion outfit complementary product retrieval by leveraging vast visual and textual data with domain knowledge. For this, a new fashion outfit dataset (acquired and curated by FARFETCH) for research and benchmark purposes is introduced. Additionally, a competitive baseline with an original negative sampling process for triplet mining was implemented and served as a starting point for participants. The top 3 performing methods are described in this paper since they constitute the reference state-of-the-art for this particular problem. To our knowledge, this is the first challenge in fashion outfit complementary product retrieval. Moreover, this joint project between academia and industry brings several relevant contributions to disseminating science and technology, promoting economic and social development, and helping to connect early-career researchers to real-world industry challenges. Springer Berlin Heidelberg 2022-12-30 2023 /pmc/articles/PMC9801353/ /pubmed/36597466 http://dx.doi.org/10.1007/s00138-022-01359-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Paper
Castro, Eduardo
Ferreira, Pedro M.
Rebelo, Ana
Rio-Torto, Isabel
Capozzi, Leonardo
Ferreira, Mafalda Falcão
Gonçalves, Tiago
Albuquerque, Tomé
Silva, Wilson
Afonso, Carolina
Gamelas Sousa, Ricardo
Cimarelli, Claudio
Daoudi, Nadia
Moreira, Gabriel
Yang, Hsiu-yu
Hrga, Ingrid
Ahmad, Javed
Keswani, Monish
Beco, Sofia
Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition
title Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition
title_full Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition
title_fullStr Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition
title_full_unstemmed Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition
title_short Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition
title_sort fill in the blank for fashion complementary outfit product retrieval: visum summer school competition
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801353/
https://www.ncbi.nlm.nih.gov/pubmed/36597466
http://dx.doi.org/10.1007/s00138-022-01359-x
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