We propose a novel step toward the unsupervised segmentation of whole objects by combining "hints" of partial scene segmentation offered by multiple soft, binary mattes....
Andrew N. Stein, Thomas S. Stepleton, Martial Hebe...
We present an approach for unsupervised segmentation of natural and textural images based on active contour, differential geometry and information theoretical concept. More precis...
In contrast to traditional Markov random field (MRF) models, we develop a Steerable Random Field (SRF) in which the field potentials are defined in terms of filter responses that ...
Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
Abstract. Complete 3-D modeling of a free-form object requires acquisition from multiple view-points. These views are then required to be registered in a common coordinate system b...