—We present a probabilistic method for segmenting instances of a particular object category within an image. Our approach overcomes the deficiencies of previous segmentation tech...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
—We propose a novel method to evaluate table segmentation results based on a table image ground truther. In the ground-truthing process, we first extract connected components fr...
—In this work, we address the problem of performing class-specific unsupervised object segmentation, i.e., automatic segmentation without annotated training images. Object segmen...
This paper presents an efficient algorithm for image segmentation and a framework for perceptual grouping. It makes an attempt to provide one way of combining bottomup and top-do...
This paper introduces a novel solver, namely cross entropy (CE), into the MRF theory for medical image segmentation. The solver, which is based on the theory of rare event simulati...