Fashion-focused creative commons social dataset

Date

2013-05-27

Author

Loni, Babak
Menendez, Maria
Georgescu, Mihai
Galli, Luca
Massari, Claudio
Altıngövde, İsmail Sengör
Martinenghi, Davide
Melenhorst, Mark
Vliegendhart, Raynor
Larson, Martha

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this work, we present a fashion-focused Creative Commons dataset, which is designed to contain a mix of general images as well as a large component of images that are focused on fashion (i.e., relevant to particular clothing items or fashion accessories). The dataset contains 4810 images and related metadata. Furthermore, a ground truth on image's tags is presented. Ground truth generation for large-scale datasets is a necessary but expensive task. Traditional expert based approaches have become an expensive and non-scalable solution. For this reason, we turn to crowdsourcing techniques in order to collect ground truth labels; in particular we make use of the commercial crowdsourcing platform, Amazon Mechanical Turk (AMT). Two different groups of annotators (i.e., trusted annotators known to the authors and crowdsourcing workers on AMT) participated in the ground truth creation. Annotation agreement between the two groups is analyzed. Applications of the dataset in different contexts are discussed. This dataset contributes to research areas such as crowdsourcing for multimedia, multimedia content analysis, and design of systems that can elicit fashion preferences from users.

Subject Keywords

Applied computing, Computers in other domains, Information systems

URI

https://hdl.handle.net/11511/34894

DOI

https://doi.org/10.1145/2483977.2483984

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

B. Loni et al., “Fashion-focused creative commons social dataset,” 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34894.