This paper develops a weakly supervised algorithm that learns to segment rigid multi-colored objects from a set of training images and key points. The approach uses congealing to ...
Douglas Moore, John Stevens, Scott Lundberg, Bruce...
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
We propose an unsupervised method for evaluating image segmentation. Common methods are typically based on evaluating smoothness within segments and contrast between them, and the...
We propose a method for segmentation of frontal human portraits from arbitrary unknown backgrounds. Semantic information is used to project the face into a normalized reference fr...
David C. Schneider, Benjamin Prestele, Peter Eiser...
With web image search engines, we face a situation where the results are very noisy, and when we ask for a specific object, we are not ensured that this object is contained in all...