Coverart for item
The Resource Compatibility modeling : data and knowledge applications for clothing matching, Xuemeng Song, Liqiang Nie, Yinglong Wang

Compatibility modeling : data and knowledge applications for clothing matching, Xuemeng Song, Liqiang Nie, Yinglong Wang

Label
Compatibility modeling : data and knowledge applications for clothing matching
Title
Compatibility modeling
Title remainder
data and knowledge applications for clothing matching
Statement of responsibility
Xuemeng Song, Liqiang Nie, Yinglong Wang
Title variation
Data and knowledge applications for clothing matching
Creator
Contributor
Author
Subject
Language
eng
Summary
Nowadays, 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
Member of
Cataloging source
CaBNVSL
http://library.link/vocab/creatorName
Song, Xuemeng
Dewey number
746.92
Illustrations
illustrations
Index
no index present
LC call number
TT507
LC item number
.S663 2020eb
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Nie, Liqiang
  • Wang, Yinglong
Series statement
Synthesis lectures on information concepts, retrieval, and services ;
Series volume
69
http://library.link/vocab/subjectName
  • Clothing and dress
  • Machine learning
  • Decision making
Target audience
  • adult
  • specialized
Label
Compatibility modeling : data and knowledge applications for clothing matching, Xuemeng Song, Liqiang Nie, Yinglong Wang
Instantiates
Publication
Note
Part of: Synthesis digital library of engineering and computer science
Bibliography note
Includes bibliographical references (pages 103-116)
Carrier category
online resource
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type MARC source
rdacontent
Contents
  • 1. Introduction -- 1.1. Background -- 1.2. Challenges -- 1.3. Our solutions -- 1.4. Book structure
  • 2. Data collection -- 2.1. Dataset I for general compatibility modeling -- 2.2. Dataset II for personalized compatibility modeling -- 2.3. Dataset III for personalized wardrobe creation -- 2.4. Summary
  • 3. Data-driven compatibility modeling -- 3.1. Introduction -- 3.2. Related work -- 3.3. Methodology -- 3.4. Experiment -- 3.5. Summary
  • 4. Knowledge-guided compatibility modeling -- 4.1. Introduction -- 4.2. Related work -- 4.3. Methodology -- 4.4. Experiment -- 4.5. Summary
  • 5. Prototype-wise interpretable compatibility modeling -- 5.1. Introduction -- 5.2. Related work -- 5.3. Methodology -- 5.4. Experiment -- 5.5. Summary
  • 6. Personalized compatibility modeling -- 6.1. Introduction -- 6.2. Related work -- 6.3. Methodology -- 6.4. Experiment -- 6.5. Summary
  • 7. Personalized capsule wardrobe creation -- 7.1. Introduction -- 7.2. Related work -- 7.3. PCW-DC -- 7.4. Body shape assignment scheme -- 7.5. Experiments -- 7.6. Summary
  • 8. Research frontiers -- 8.1. Generative compatibility modeling -- 8.2. Virtual try-on with arbitrary pose -- 8.3. Clothing generation
Control code
201909ICR069
Dimensions
unknown
Extent
1 PDF (xix, 118 pages)
File format
multiple file formats
Form of item
online
Isbn
9781681736693
Media category
electronic
Media MARC source
isbdmedia
Other physical details
color illustrations.
Reformatting quality
access
Specific material designation
remote
System control number
  • (CaBNVSL)thg00979752
  • (OCoLC)1129091766
Label
Compatibility modeling : data and knowledge applications for clothing matching, Xuemeng Song, Liqiang Nie, Yinglong Wang
Publication
Note
Part of: Synthesis digital library of engineering and computer science
Bibliography note
Includes bibliographical references (pages 103-116)
Carrier category
online resource
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type MARC source
rdacontent
Contents
  • 1. Introduction -- 1.1. Background -- 1.2. Challenges -- 1.3. Our solutions -- 1.4. Book structure
  • 2. Data collection -- 2.1. Dataset I for general compatibility modeling -- 2.2. Dataset II for personalized compatibility modeling -- 2.3. Dataset III for personalized wardrobe creation -- 2.4. Summary
  • 3. Data-driven compatibility modeling -- 3.1. Introduction -- 3.2. Related work -- 3.3. Methodology -- 3.4. Experiment -- 3.5. Summary
  • 4. Knowledge-guided compatibility modeling -- 4.1. Introduction -- 4.2. Related work -- 4.3. Methodology -- 4.4. Experiment -- 4.5. Summary
  • 5. Prototype-wise interpretable compatibility modeling -- 5.1. Introduction -- 5.2. Related work -- 5.3. Methodology -- 5.4. Experiment -- 5.5. Summary
  • 6. Personalized compatibility modeling -- 6.1. Introduction -- 6.2. Related work -- 6.3. Methodology -- 6.4. Experiment -- 6.5. Summary
  • 7. Personalized capsule wardrobe creation -- 7.1. Introduction -- 7.2. Related work -- 7.3. PCW-DC -- 7.4. Body shape assignment scheme -- 7.5. Experiments -- 7.6. Summary
  • 8. Research frontiers -- 8.1. Generative compatibility modeling -- 8.2. Virtual try-on with arbitrary pose -- 8.3. Clothing generation
Control code
201909ICR069
Dimensions
unknown
Extent
1 PDF (xix, 118 pages)
File format
multiple file formats
Form of item
online
Isbn
9781681736693
Media category
electronic
Media MARC source
isbdmedia
Other physical details
color illustrations.
Reformatting quality
access
Specific material designation
remote
System control number
  • (CaBNVSL)thg00979752
  • (OCoLC)1129091766

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