In this paper, we investigate a search-based face annotation framework by mining weakly labeled facial images that are freely available on the internet. A key component of such a ...
Learning semantics from annotated images to enhance content-based retrieval is an important research direction. In this paper, annotation data are assumed available for only a sub...
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
In this paper, we demonstrate a novel landmark photo search and browsing system, Agate, which ranks landmark image search results considering their relevance, diversity and qualit...
Yuheng Ren, Mo Yu, Xin-Jing Wang, Lei Zhang, Wei-Y...
Relevance feedback (RF) has been extensively studied in the content-based image retrieval community. However, no commercial Web image search engines support RF because of scalabil...