Annotation Propagation in Large Image Databases via Dense Image Correspondence
نویسندگان
چکیده
Prior Work This Work Large training set of densely labeled images Weakly supervised setup: use both image tags (cheaper to obtain) and labeled pixels (expensive to obtain) Each image classified independently Solve jointly for all pixels and classes Use dense image correspondences to resolve visual ambiguities Fully tagged and labeled image database Sparsely tagged and (even not) labeled image database Algorithm
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تاریخ انتشار 2012