Weakly supervised discovery of common visual structure in highly variable, cluttered images is a key problem in recognition. We address this problem using deformable part-based mo...
We introduce a saliency model based on two key ideas. The first one is considering local and global image patch rarities as two complementary processes. The second one is based o...
Background: The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional l...
: Integration of heterogeneous information in the context of Internet becomes a key activity to enable a more organized and semantically meaningful access to data sources. As Inter...
We present a discriminative shape-based algorithm for object category localization and recognition. Our method learns object models in a weakly-supervised fashion, without requiri...
Marius Leordeanu, Martial Hebert, Rahul Sukthankar