{\rtf1\ansi\deff0\deftab360 {\fonttbl {\f0\fswiss\fcharset0 Arial} {\f1\froman\fcharset0 Times New Roman} {\f2\fswiss\fcharset0 Verdana} {\f3\froman\fcharset2 Symbol} } {\colortbl; \red0\green0\blue0; } {\info {\author Biblio 7.x}{\operator }{\title Biblio RTF Export}} \f1\fs24 \paperw11907\paperh16839 \pgncont\pgndec\pgnstarts1\pgnrestart Stefanoiu, A, Weinmann, A, Storath, M, Navab, N and Baust, M (2016). Joint Segmentation and Shape Regularization with a Generalized Forward Backward Algorithm. IEEE Transactions on Image Processing. 25 3384 - 3394\par \par Zheng, S, Cheng, M Ming, Warrell, J, Sturgess, P, Vineet, V, Rother, C and Torr, P H S (2014). Dense semantic image segmentation with objects and attributes. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3214?3221. http://www.robots.ox.ac.uk/?tvg/http://tu-dresden.de/inf/cvld\par \par M\'e1rquez-Neila, P, Kohli, P, Rother, C and Baumela, L (2014). Non-parametric higher-order random fields for image segmentation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8694 LNCS 269?284\par \par Lempitsky, V, Blake, A and Rother, C (2012). Branch-and-mincut: Global optimization for image segmentation with high-level priors. Journal of Mathematical Imaging and Vision. 44 315?329\par \par Kohli, P, Nickisch, H, Rother, C and Rhemann, C (2012). User-centric learning and evaluation of interactive segmentation systems. International Journal of Computer Vision. 100 261?274\par \par Ding, L and Yilmaz, A (2010). Interactive image segmentation using probabilistic hypergraphs. Pattern Recognition. 43 1863?1873. http://www.research.microsoft.com/vision/cambridge\par \par }