Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
We introduce an online learning approach for multitarget tracking. Detection responses are gradually associated into tracklets in multiple levels to produce final tracks. Unlike ...
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 describe an algorithm for similar-image search which
is designed to be efficient for extremely large collections of
images. For each query, a small response set is selected by...
Lorenzo Torresani (Dartmouth College), Martin Szum...
We introduce a new class of image features, the Ray feature set, that consider image characteristics
at distant contour points, capturing information which is difficult to repre...