In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
We address the problem of label assignment in computer
vision: given a novel 3-D or 2-D scene, we wish to assign a
unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
Dimensionality reduction is the problem of finding a low-dimensional representation of highdimensional input data. This paper examines the case where additional information is kno...
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
We consider the problem of computing stereo correspondence for scenes dense in physical structure, such as a bouquet of flowers. Boundaries are then space curves, formally govern...