Subdiv17: a dataset for investigating subjectivity in the visual diversification of image search results.

MMSys '18: 9th ACM Multimedia Systems Conference Amsterdam Netherlands June, 2018(2018)

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摘要
In this paper, we present a new dataset that facilitates the comparison of approaches aiming at the diversification of image search results. The dataset was explicitly designed for general-purpose, multi-topic queries and provides multiple ground truth annotations to allow for the exploration of the subjectivity aspect in the general task of diversification. The dataset provides images and their metadata retrieved from Flickr for around 200 complex queries. Additionally, to encourage experimentations (and cooperations) from different communities such as information and multimedia retrieval, a broad range of pre-computed descriptors is provided. The proposed dataset was successfully validated during the MediaEval 2017 Retrieving Diverse Social Images task using 29 submitted runs.
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关键词
Benchmark dataset, search result diversification, image retrieval, annotation subjectivity, MediaEval, Flickr
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