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Geolocalized databases are becoming necessary in a wide variety of application domains. Thus far, the creation of such databases has been a costly, manual process. This drawback has stimulated interest in automating their construction, for example, by mining geographical information from the Web. Here we present and evaluate a new automated technique for(More)
ImageCLEF's Flickr Photo Annotation and Retrieval task aims to advance the state of the art in multimedia research by providing a challenging benchmark for visual concept detection, annotation and retrieval in the context of a diverse collection of Flickr photos. The benchmark consisted of two separate but closely connected subtasks, where the objective of(More)
This paper provides an overview of the Retrieving Diverse Social Images task that is organized as part of the MediaEval 2014 Benchmarking Initiative for Multimedia Evaluation. The task addresses the problem of result diversification in the context of social photo retrieval. We present the task challenges, the proposed data set and ground truth, the required(More)
This paper provides an overview of the Retrieving Diverse Social Images task that is organized as part of the MediaEval 2015 Benchmarking Initiative for Multimedia Evaluation. The task addresses the problem of result diversification and user annotation credibility estimation in the context of social photo retrieval. We present the task challenges, the(More)
Web image search is inspired by text search techniques; it mainly relies on indexing textual data that surround the image file. But retrieval results are often noisy and image processing techniques have been proposed to rerank images. Unfortunately, these techniques usually imply a computational overload that makes the reranking process intractable in real(More)
This paper provides an overview of the Retrieving Diverse Social Images task that is organized as part of the MediaEval 2013 Benchmarking Initiative for Multimedia Evaluation. The task addresses the problem of result diversification in the context of social photo retrieval. We present the task challenges, the proposed data set and ground truth, the required(More)
The automatic attribution of semantic labels to unlabeled or weakly labeled images has received considerable attention but, given the complexity of the problem, remains a hard research topic. Here we propose a unified classification framework which mixes textual and visual information in a seamless manner. Unlike most recent previous works, computer vision(More)