In this paper, we propose a new transductive learning framework for image retrieval, in which images are taken as vertices in a weighted hypergraph and the task of image search is...
This work presents a discriminative model for the retrieval of pictures from text queries. The core idea of this approach is to minimize a loss directly related to the retrieval pe...
In this demo, we present a system called iRIN designed for performing image retrieval in image-rich information networks. We first introduce MoK-SimRank to significantly improve...
Xin Jin, Jiebo Luo, Jie Yu, Gang Wang, Dhiraj Josh...
This paper investigates the problem of learning the visual semantics of keyword categories for automatic image annotation. Supervised learning algorithms which learn only a single ...
In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. Thes...