Many computer vision tasks may be expressed as the problem of learning a mapping between image space and a parameter space. For example, in human body pose estimation, recent rese...
Ramanan Navaratnam, Andrew W. Fitzgibbon, Roberto ...
Unlike most previous manifold-based data classification algorithms assume that all the data points are on a single manifold, we expect that data from different classes may reside ...
This paper describes an approach for using several levels of data fusion in the domain of autonomous off-road navigation. We are focusing on outdoor obstacle detection, and we pre...
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. But a major obstacle to this is the insufficienc...
Training datasets for learning of object categories are often contaminated or imperfect. We explore an approach to automatically identify examples that are noisy or troublesome fo...
Anelia Angelova, Yaser S. Abu-Mostafa, Pietro Pero...