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Co-reranking by mutual reinforcement for image search
Proceedings of the ACM International Conference on Image and Video Retrieval - CIVR '10
Most existing reranking approaches to image search focus solely on mining "visual" cues within the initial search results. However, the visual information cannot always provide enough guidance to the reranking process. For example, different images with similar appearance may not always present the same relevant information to the query. Observing that multi-modality cues carry complementary relevant information, we propose the idea of co-reranking for image search, by jointly exploring thedoi:10.1145/1816041.1816048 dblp:conf/civr/YaoMN10 fatcat:6jeidijmmbbm3cqeb7sx5jwpam