Given an image, we propose a hierarchical generative
model that classifies the overall scene, recognizes and segments
each object component, as well as annotates the image
with ...
We propose a new framework for multi-object segmentation of deep brain structures, which have significant shape variations and relatively small sizes in medical brain images. In th...
We address the task of learning a semantic segmentation from weakly supervised data. Our aim is to devise a system that predicts an object label for each pixel by making use of on...
Abstract. Level set methods are a popular way to solve the image segmentation problem in computer image analysis. A contour is implicitly represented by the zero level of a signed ...
Abstract. We propose a novel algorithm called graph-shifts for performing image segmentation and labeling. This algorithm makes use of a dynamic hierarchical representation of the ...
Jason J. Corso, Zhuowen Tu, Alan L. Yuille, Arthur...