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Fashion 10000: an enriched social image dataset for fashion and clothing

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Martha LarsonAuthors Info & Claims

MMSys '14: Proceedings of the 5th ACM Multimedia Systems Conference

Pages 41 - 46

https://doi.org/10.1145/2557642.2563675

Published: 19 March 2014 Publication History

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Abstract

In this work, we present a new social image dataset related to the fashion and clothing domain. The dataset contains more than 32000 images, their context and social metadata. Furthermore the dataset is enriched with several types of annotations collected from the Amazon Mechanical Turk (AMT) crowdsourcing platform, which can serve as ground truth for various content analysis algorithms. This dataset has been successfully used at the Crowdsourcing task of the 2013 MediaEval Multimedia Benchmarking initiative. The dataset contributes to several research areas such as Crowdsourcing, multimedia content and context analysis as well as hybrid human/automatic approaches. In this paper, the dataset is described in detail and the dataset collection strategy, statistics, applications of dataset and its contribution to MediaEval 2013 is discussed.

References

[1]

M. J. Huiskes and M. S. Lew. The mir flickr retrieval evaluation. In MIR '08: Proceedings of the 2008 ACM International Conference on Multimedia Information Retrieval, New York, NY, USA, 2008. ACM.

Digital Library

Google Scholar

[2]

S. Liu, J. Feng, Z. Song, T. Zhang, H. Lu, C. Xu, and S. Yan. Hi, magic closet, tell me what to wear! In Proceedings of the 20th ACM International Conference on Multimedia, New York, NY, USA, 2012. ACM.

Digital Library

Google Scholar

[3]

B. Loni, M. Larson, A. Bozzon, and L. Gottlieb. Crowdsourcing for social multimedia at mediaeval 2013: Challenges, data set, and evaluation. In MediaEval 2013 Workshop, Barcelona, Spain, 2013.

Google Scholar

[4]

B. Loni, M. Menendez, M. Georgescu, L. Galli, C. Massari, I. S. Altingovde, D. Martinenghi, M. Melenhorst, R. Vliegendhart, and M. Larson. Fashion-focused creative commons social dataset. In Proceedings of the 4th ACM Multimedia Systems Conference, New York, NY, USA, 2013. ACM.

Digital Library

Google Scholar

[5]

S. Nowak and S. Rüger. How reliable are annotations via crowdsourcing: a study about inter-annotator agreement for multi-label image annotation. In Proceedings of the international conference on Multimedia information retrieval. ACM, 2010.

Digital Library

Google Scholar

[6]

J. J. Randolph, A. Thanks, R. Bednarik, and N. Myller. Free-marginal multirater kappa (multirater κfree): an alternative to fleissąę fixed-marginal multirater kappa. In Joensuu learning and instruction symposium. Citeseer, 2005.

Google Scholar

[7]

M. Riegler, M. Lux, and C. Kofler. Frame the crowd: Global visual features labeling boosted with crowdsourcing information. In MediaEval 2013 Workshop, Barcelona, Spain, 2013.

Google Scholar

[8]

R. Sakurai, J.-H. Lee, and K. Kawagoe. People and clothes recognition based on topic model. In System Integration (SII), 2011 IEEE/SICE International Symposium on, 2011.

Crossref

Google Scholar

[9]

L. Von Ahn. Games with a purpose. Computer, 39(6):92--94, 2006.

Digital Library

Google Scholar

[10]

K. Yamaguchi. Parsing clothing in fashion photographs. In Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), CVPR '12, Washington, DC, USA, 2012. IEEE Computer Society.

Digital Library

Google Scholar

Cited By

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P. Anusha Kandula Nikhil Saradhi Kokkirala Sravan Kumar Marisetty Tejesh (2024)Fashion Recommendation System Using Social Media WebsiteInternational Journal of Advanced Research in Science, Communication and Technology10.48175/IJARSCT-22093(509-517)Online publication date: 30-Nov-2024
https://doi.org/10.48175/IJARSCT-22093
Borgersen KGoodwin MGrundetjern MSharma J(2024)A Dataset for Adapting Recommender Systems to the Fashion Rental EconomyProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3688174(945-950)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3688174
Islam SJoardar SSekh A(2024)BangleFIR: bridging the gap in fashion image retrieval with a novel dataset of banglesMultimedia Tools and Applications10.1007/s11042-024-19698-4Online publication date: 10-Jul-2024
https://doi.org/10.1007/s11042-024-19698-4
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Index Terms

Fashion 10000: an enriched social image dataset for fashion and clothing
1. Applied computing
  1. Computers in other domains
    1. Digital libraries and archives
2. Information systems
  1. Information retrieval
    1. Document representation
      1. Document collection models
  2. Information systems applications
    1. Digital libraries and archives

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Published In

MMSys '14: Proceedings of the 5th ACM Multimedia Systems Conference

March 2014

323 pages

ISBN:9781450327053

DOI:10.1145/2557642

General Chair:
Roger Zimmermann
National University of Singapore, Singapore

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 March 2014

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Research-article

Funding Sources

Lakeside Labs GmbH, Klagenfurt, Austria
National Science Council Taiwan
European Regional Development Fund
Carinthian Economic Promotion Fund (KWF)

Conference

MMSys '14

Sponsor:

MMSys '14: Multimedia Systems Conference 2014

March 19, 2014

Singapore, Singapore

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MMSys '14 Paper Acceptance Rate 15 of 57 submissions, 26%;

Overall Acceptance Rate 176 of 530 submissions, 33%

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Cited By

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P. Anusha Kandula Nikhil Saradhi Kokkirala Sravan Kumar Marisetty Tejesh (2024)Fashion Recommendation System Using Social Media WebsiteInternational Journal of Advanced Research in Science, Communication and Technology10.48175/IJARSCT-22093(509-517)Online publication date: 30-Nov-2024
https://doi.org/10.48175/IJARSCT-22093
Borgersen KGoodwin MGrundetjern MSharma J(2024)A Dataset for Adapting Recommender Systems to the Fashion Rental EconomyProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3688174(945-950)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3688174
Islam SJoardar SSekh A(2024)BangleFIR: bridging the gap in fashion image retrieval with a novel dataset of banglesMultimedia Tools and Applications10.1007/s11042-024-19698-4Online publication date: 10-Jul-2024
https://doi.org/10.1007/s11042-024-19698-4
Kouslis EPapachristou EStavropoulos TPapazoglou Chalikias AChatzilari ENikolopoulos SKompatsiaris I(2024)AI in fashion: a literature reviewElectronic Commerce Research10.1007/s10660-024-09872-zOnline publication date: 19-Jun-2024
https://doi.org/10.1007/s10660-024-09872-z
Su MWang MWang Z(2023)BigFashion: A Large-Scale Dataset for Fine-Grained Attributes Recognition2023 IEEE 23rd International Conference on Communication Technology (ICCT)10.1109/ICCT59356.2023.10419642(1-7)Online publication date: 20-Oct-2023
https://doi.org/10.1109/ICCT59356.2023.10419642
Islam SJoardar SSekh A(2023)Ornament image retrieval using few-shot learningInternational Journal of Multimedia Information Retrieval10.1007/s13735-023-00299-012:2Online publication date: 31-Aug-2023
https://doi.org/10.1007/s13735-023-00299-0
Wazarkar SKeshavamurthy BSequeira E(2023)Socio-fashion Dataset: A Fashion Attribute Data Generated Using Fashion-Related Social ImagesHybrid Intelligent Systems10.1007/978-3-031-27409-1_31(350-356)Online publication date: 25-May-2023
https://doi.org/10.1007/978-3-031-27409-1_31
Islam SJoardar SSekh A(2023)NecklaceFIR: A Large Volume Benchmarked Necklace Dataset for Fashion Image RetrievalArtificial Intelligence10.1007/978-3-031-22485-0_17(180-190)Online publication date: 1-Jan-2023
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Mameli MPaolanti MPietrini RPazzaglia GFrontoni EZingaretti P(2022)Deep Learning Approaches for Fashion Knowledge Extraction From Social Media: A ReviewIEEE Access10.1109/ACCESS.2021.313789310(1545-1576)Online publication date: 2022
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Wu YWeimer JDavidson S(2021)CHEFProceedings of the VLDB Endowment10.14778/3476249.347629014:11(2410-2418)Online publication date: 27-Oct-2021
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