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008			230411s2020 sz | s |||| 0|eng d
020			_a9783031023217
024	7		_a10.1007/978-3-031-02321-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTT507 _b2020 EB
100	1		_aSong, Xuemeng _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686433
245	1	0	_aCompatibility Modeling : _bData and Knowledge Applications for Clothing Matching _cby Xuemeng Song, Liqiang Nie, Yinglong Wang
250			_a1st edition 2020
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XIX, 118 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Information Concepts Retrieval and Services _x1947-9468
505	0		_aPreface -- Acknowledgments -- Introduction -- Data Collection -- Data-Driven Compatibility Modeling -- Knowledge-Guided Compatibility Modeling -- Prototype-Wise Interpretable Compatibility Modeling -- Personalized Compatibility Modeling -- Personalized Capsule Wardrobe Creation -- Research Frontiers -- Bibliography -- Authors' Biographies.
520			_aNowadays, fashion has become an essential aspect of people's daily life. As each outfit usually comprises several complementary items, such as a top, bottom, shoes, and accessories, a proper outfit largely relies on the harmonious matching of these items. Nevertheless, not everyone is good at outfit composition, especially those who have a poor fashion aesthetic. Fortunately, in recent years the number of online fashion-oriented communities, like IQON and Chictopia, as well as e-commerce sites, like Amazon and eBay, has grown. The tremendous amount of real-world data regarding people's various fashion behaviors has opened a door to automatic clothing matching. Despite its significant value, compatibility modeling for clothing matching that assesses the compatibility score for a given set of (equal or more than two) fashion items, e.g., a blouse and a skirt, yields tough challenges: (a) the absence of comprehensive benchmark; (b) comprehensive compatibility modeling with the multi-modal feature variables is largely untapped; (c) how to utilize the domain knowledge to guide the machine learning; (d) how to enhance the interpretability of the compatibility modeling; and (e) how to model the user factor in the personalized compatibility modeling. These challenges have been largely unexplored to date. In this book, we shed light on several state-of-the-art theories on compatibility modeling. In particular, to facilitate the research, we first build three large-scale benchmark datasets from different online fashion websites, including IQON and Amazon. We then introduce a general data-driven compatibility modeling scheme based on advanced neural networks. To make use of the abundant fashion domain knowledge, i.e., clothing matching rules, we next present a novel knowledge-guided compatibility modeling framework. Thereafter, to enhance the model interpretability, we put forward a prototype-wise interpretable compatibility modeling approach. Following that, noticing the subjective aesthetics of users, we extend the general compatibility modeling to the personalized version. Moreover, we further study the real-world problem of personalized capsule wardrobe creation, aiming to generate a minimum collection of garments that is both compatible and suitable for the user. Finally, we conclude the book and present future research directions, such as the generative compatibility modeling, virtual try-on with arbitrary poses, and clothing generation.
988			_aSynthesis Collection of Technology_2020
650		7	_2embne _9142336 _aDiseño de moda
650		7	_2embne _9166090 _aAprendizaje automático
650		7	_2embne _9141176 _aToma de decisiones
700	1		_aNie, Liqiang _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686432
700	1		_aWang, Yinglong _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9688049 _c(Researcher)
776	0	8	_iPrinted edition: _z9783031002281
776	0	8	_iPrinted edition: _z9783031011931
776	0	8	_iPrinted edition: _z9783031034497
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02321-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b04/2023 _dz _eIG _zSI