This paper presents a new approach to discriminative modeling for classi cation and labeling. Our method, called Boosting on Multilevel Aggregates (BMA), adds a new class of hiera...
Belief Propagation (BP) can be very useful and efficient for performing approximate inference on graphs. But when the graph is very highly connected with strong conflicting intera...
We present a novel approach for multi-object tracking which considers object detection and spacetime trajectory estimation as a coupled optimization problem. It is formulated in a...
The standard graph cut technique is a robust method for globally optimal image segmentations. However, because of its global nature, it is prone to capture outlying areas similar ...
Camera calibration is a primary crucial step in many computer vision tasks. In this paper we present a new neural approach for camera calibration. Unlike some existing neural appr...