The MIR Flickr collection consists of 25000 high-quality photographic images of thousands of Flickr users, made available under the Creative Commons license. The database includes all the original user tags and EXIF metadata. Additionally, detailed and accurate annotations are provided for topics corresponding to the most prominent visual concepts in the user tag data. The rich metadata allow for a wide variety of image retrieval benchmarking scenarios. In this paper, we provide an overview of the various strategies that were devised for automatic visual concept detection using the MIR Flickr collection. In particular we discuss results from various experiments in combining social data and low-level content-based descriptors to improve the ...
iAvatar is an existing Tag-based Social Image Retrieval system. At present, it allows users to searc...
This paper seeks to unravel whether commonly available social tagged images can be exploited as a tr...
With the rapidly increasing popularity of Social Media sites, a lot of user generated content has be...
The MIR Flickr collection consists of 25000 high-quality photographic images of thousands of Flickr ...
International audienceIn this paper we present the common effort of Lear and XRCE for the ImageCLEF ...
Searching for the co-occurrence of two visual concepts in unlabeled images is an important step towa...
mageCLEF introduced its first automatic annotation task for photos in 2006. The visual object and co...
This paper presents the first participation of the Pattern Recognition and Application Group (PRA Gr...
In light of the strong demands for semantic search over large-scale consumer photos, which generally...
The ImageCLEF 2011 Photo Annotation and Concept-based Retrieval Tasks pose the challenge of an autom...
Abstract. The ImageCLEF 2011 Photo Annotation and Concept-based Retrieval Tasks pose the challenge o...
In most well known image retrieval test sets, the imagery typically cannot be freely distributed or ...
International audienceThe text associated with images provides valuable semantic meanings about imag...
This paper describes the participation of the Web Science Laboratory of Meiji University in the Imag...
Abstract. The task of visual concept detection, annotation, and retrieval using Flickr photos at Ima...
iAvatar is an existing Tag-based Social Image Retrieval system. At present, it allows users to searc...
This paper seeks to unravel whether commonly available social tagged images can be exploited as a tr...
With the rapidly increasing popularity of Social Media sites, a lot of user generated content has be...
The MIR Flickr collection consists of 25000 high-quality photographic images of thousands of Flickr ...
International audienceIn this paper we present the common effort of Lear and XRCE for the ImageCLEF ...
Searching for the co-occurrence of two visual concepts in unlabeled images is an important step towa...
mageCLEF introduced its first automatic annotation task for photos in 2006. The visual object and co...
This paper presents the first participation of the Pattern Recognition and Application Group (PRA Gr...
In light of the strong demands for semantic search over large-scale consumer photos, which generally...
The ImageCLEF 2011 Photo Annotation and Concept-based Retrieval Tasks pose the challenge of an autom...
Abstract. The ImageCLEF 2011 Photo Annotation and Concept-based Retrieval Tasks pose the challenge o...
In most well known image retrieval test sets, the imagery typically cannot be freely distributed or ...
International audienceThe text associated with images provides valuable semantic meanings about imag...
This paper describes the participation of the Web Science Laboratory of Meiji University in the Imag...
Abstract. The task of visual concept detection, annotation, and retrieval using Flickr photos at Ima...
iAvatar is an existing Tag-based Social Image Retrieval system. At present, it allows users to searc...
This paper seeks to unravel whether commonly available social tagged images can be exploited as a tr...
With the rapidly increasing popularity of Social Media sites, a lot of user generated content has be...