Hierarchical clustering of WWW image search results using visual, textual and link information
Proceedings of the 12th annual ACM international conference on Multimedia
Video search reranking through random walk over document-level context graph
Proceedings of the 15th international conference on Multimedia
Generating diverse and representative image search results for landmarks
Proceedings of the 17th international conference on World Wide Web
Image clustering based on a shared nearest neighbors approach for tagged collections
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
VisualRank: Applying PageRank to Large-Scale Image Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian video search reranking
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Visual diversification of image search results
Proceedings of the 18th international conference on World wide web
Jointly optimising relevance and diversity in image retrieval
Proceedings of the ACM International Conference on Image and Video Retrieval
Overview of the ImageCLEFphoto 2008 photographic retrieval task
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Dual-ranking for web image retrieval
Proceedings of the ACM International Conference on Image and Video Retrieval
A hybrid unsupervised image re-ranking approach with latent topic contents
Proceedings of the ACM International Conference on Image and Video Retrieval
Image retrieval systems based on compact shape descriptor and relevance feedback information
Journal of Visual Communication and Image Representation
Dynamic two-stage image retrieval from large multimodal databases
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Actions in stillweb images: visualization, detection and retrieval
WAIM'11 Proceedings of the 12th international conference on Web-age information management
Content based image retrieval using visual-words distribution entropy
MIRAGE'11 Proceedings of the 5th international conference on Computer vision/computer graphics collaboration techniques
Video summarization using a self-growing and self-organized neural gas network
MIRAGE'11 Proceedings of the 5th international conference on Computer vision/computer graphics collaboration techniques
Dynamic two-stage image retrieval from large multimedia databases
Information Processing and Management: an International Journal
Multimodal re-ranking of product image search results
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Multimedia search reranking: A literature survey
ACM Computing Surveys (CSUR)
SalientShape: group saliency in image collections
The Visual Computer: International Journal of Computer Graphics
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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 time. We introduce here a lightweight reranking method that compares each result not only to the other query results but also to an external, contrastive class of items. The external class contains diversified images; the intuition supporting our approach is that results that are visually similar to other query results but dissimilar to elements of the contrastive class are likely to be good answers. The success of visual reranking depends on the visual coherence of queries; we measure this coherence in order to evaluate the chances of success. Visual reranking tends to emerge near duplicate images and we complement it with a diversification function which ensures that different aspects of a query are presented to the user. Our method is evaluated against a standard search engine using 210 diversified queries. Significant improvements are reported for both quantitative and qualitative tests.