Other Interests • Music: Violine, guitar, singing. • Sports: Triathlon, marathon, race biking, mountain climbing. 4
Scientific Publications All papers can be downloaded from www.gpu4vision.org Journal Papers [1] T. <strong>Pock</strong>, M. <strong>Pock</strong>, and H. Bisch<strong>of</strong>. Algorithmic differentiation: Application to variational problems in computer vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(7):1180–1193, 2007. [2] C. Bauer, T. <strong>Pock</strong>, R. Beichel, E. Sorantin, and H. Bisch<strong>of</strong>. Segmentation <strong>of</strong> interwoven 3D tubular tree structures utilizing shape priors and graph cuts. Medical Image Analysis, 2009. [3] K. Bredies, K. Kunisch, and T. <strong>Pock</strong>. Total generalized variation. SIAM Journal on Imaging Sciences, 3(3):492–526, 2010. [4] A. Chambolle and T. <strong>Pock</strong>. A first-order primal-dual algorithm for convex problems with applications to imaging. Journal <strong>of</strong> Mathematical Imaging and Vision, 40(1):120–145, 2010. [5] F. Knoll, M. Unger, C. Diwoky, C. Clason, T. <strong>Pock</strong>, and R. Stollberger. Fast reduction <strong>of</strong> undersampling artifacts in radial MR angiography with 3D total variation on graphics hardware. Magnetic Resonance Materials in Physics, Biology and Medicine, 23(2):103–114, 2010. [6] F. Leberl, H. Bisch<strong>of</strong>, T. <strong>Pock</strong>, A. Irschara, and S. Kluckner. Aerial computer vision for a 3D virtual habitat. Computer, 43:24–31, 2010. [7] F. Leberl, A. Irschara, T. <strong>Pock</strong>, P. Meixner, M. Gruber, S. Scholz, and A. Wiechert. LIDAR versus 3D vision. Photogrammetric Engineering and Remote Sensing, 2010. [8] T. <strong>Pock</strong>, D. Cremers, H. Bisch<strong>of</strong>, and A. Chambolle. Global solutions <strong>of</strong> variational models with convex regularization. SIAM Journal on Imaging Sciences, 3(4):1122–1145, 2010. [9] F. Knoll, K. Bredies, T. <strong>Pock</strong>, and R. Stollberger. Second order total generalized variation (TGV) for MRI. Magnetic Resonance in Medicine, 2011. [10] K. Bredies, T. <strong>Pock</strong>, and B. Wirth. Convex relaxation <strong>of</strong> a class <strong>of</strong> vertex penalizing functionals. Journal <strong>of</strong> Mathematical Imaging and Vision, 2012. accepted for publication. [11] A. Chambolle, D. Cremers, and T. <strong>Pock</strong>. A convex approach to minimal partitions. SIAM Journal on Imaging Sciences, 2012. accepted for publication. Book Chapters [12] A. Chambolle, V. Caselles, D. Cremers, M. Novaga, and T. <strong>Pock</strong>. An introduction to total variation for image analysis. In Theoretical Foundations and Numerical Methods for Sparse Recovery. De Gruyter, 2010. [13] D. Cremers, T. <strong>Pock</strong>, K. Kolev, and A. Chambolle. Convex relaxation techniques for segmentation, stereo and multiview reconstruction. In Advances in Markov Random Fields for Vision and Image Processing. MIT Press, 2011. [14] T. <strong>Pock</strong>, L. Zebedin, and H. Bisch<strong>of</strong>. TGV-fusion. In Rainbow <strong>of</strong> Computer Science. Springer-Verlag, 2011. to appear. 5
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