In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of training images labeled ...
This work explores the problem of cross-lingual pairwise similarity, where the task is to extract similar pairs of documents across two different languages. Solutions to this pro...
We develop a local image-correspondence algorithm which performs well near occluding boundaries. Unlike traditional robust methods, our method can find correspondences when the on...
The importance of named entities in information retrieval and knowledge management has recently brought interest in characterizing semantic relationships between entities. In this...
A novel and general criterion for image similarity validation is introduced using the so-called a contrario decision framework. It is mathematically proved that it is possible to c...