In this paper, we exploit a novel ranking mechanism that processes query samples with noisy labels, motivated by the practical application of web image search re-ranking where the...
With web image search engines, we face a situation where the results are very noisy, and when we ask for a specific object, we are not ensured that this object is contained in all...
Web image search engine has become an important tool to organize digital images on the Web. However, most commercial search engines still use a list presentation while little effo...
We consider the problem of clustering Web image search results. Generally, the image search results returned by an image search engine contain multiple topics. Organizing the resu...
Deng Cai, Xiaofei He, Zhiwei Li, Wei-Ying Ma, Ji-R...
The rapid development of web image search engines has enabled users to search hundred million of images available on the Web. However, due to the unsatisfactory performance of cur...
Web image search has been explored and developed in academic as well as commercial areas for over a decade. To measure the similarity between Web images and user queries, most of ...
Ying Liu, Tao Qin, Tie-Yan Liu, Lei Zhang, Wei-Yin...
In this demo, we present IGroup, a Web image search engine that organizes the search results into semantic clusters. Different from all existing Web image search results clusterin...
In general, digital images can be classified into photographs and computer graphics. This taxonomy is very useful in many applications, such as web image search. However, there ar...
Current web image search engines still rely on user typing textual description: query word(s) for visual targets. As the queries are often short, general or even ambiguous, the im...
Shuo Wang, Feng Jing, Jibo He, Qixing Du, Lei Zhan...
Web image search is difficult in part because a handful of keywords are generally insufficient for characterizing the visual properties of an image. Popular engines have begun to ...
James Fogarty, Desney S. Tan, Ashish Kapoor, Simon...