Pregled bibliografske jedinice broj: 1251581
Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition
Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition // Machine Vision and Applications, 34 (2023), 1; 16, 15 doi:10.1007/s00138-022-01359-x (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1251581 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Fill in the blank for fashion complementary
outfit
product Retrieval: VISUM summer school
competition
Autori
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
Izvornik
Machine Vision and Applications (0932-8092) 34
(2023), 1;
16, 15
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Image retrieval, Summer school competition, Computer vision, Deep learning, Fashion intelligence
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus