Paper Info
Title
Fashion 10000: an enriched social image dataset for fashion and clothing
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.
Year
DOI
Venue
2014
10.1145/2557642.2563675
MMSys
Keywords
Field
DocType
amazon mechanical turk,social metadata,enriched social image dataset,multimedia content,dataset collection strategy,automatic approach,crowdsourcing task,context analysis,various content analysis algorithm,mediaeval multimedia benchmarking initiative,new social image dataset,clothing
Data science,Metadata,Content analysis,Information retrieval,Crowdsourcing,Context analysis,Computer science,Clothing,Real-time computing,Ground truth,Social image,Benchmarking
Conference
Citations 
PageRank 
References 
16
0.78
8
Authors
6
Name
Order
Citations
PageRank
Babak Loni114410.77
Lei Yen Cheung2160.78
Michael Riegler3605.05
Alessandro Bozzon464171.27
Luke Gottlieb5615.79
Martha Larson61661116.07