The Journal of Machine Learning Research
Learning to cluster web search results
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Efficient propagation for face annotation in family albums
Proceedings of the 12th annual ACM international conference on Multimedia
AnnoSearch: Image Auto-Annotation by Search
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Scalable search-based image annotation of personal images
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Image annotation by large-scale content-based image retrieval
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Learning tag relevance by neighbor voting for social image retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Argo: intelligent advertising made possible from users' photos
MM '09 Proceedings of the 17th ACM international conference on Multimedia
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In this technical demonstration, we showcase the SBIA system - a search-based image annotation system. At the heart of the system lies a very large-scale image search engine which indexed three million Web images and supports both text and visual queries. Given an image (with initial annotations), SBIA first finds semantically/visually similar images via the search engine, and then mines representative keywords from the retrieved images. These keywords, after annotation rejection and relevance ranking, are finally used to annotate the query image.