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Journal Article

J. Yuan, Schnörr, C., and Mémin, E., “Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation”, J.~Math.~Imag.~Vision, vol. 28, pp. 67-80, 2007.

Technical Report (752.44 KB)

J. Lellmann, Lellmann, B., Widmann, F., and Schnörr, C., “Discrete and Continuous Models for Partitioning Problems”, Int.~J.~Comp.~Visionz, vol. 104, pp. 241-269, 2013.

Technical Report (4.74 MB)

D. Cremers, Tischhäuser, F., Weickert, J., and Schnörr, C., “Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford–Shah functional”, Int. J. Computer Vision, vol. 50, pp. 295–313, 2002.

S. Petra, Schnörr, C., and Schröder, A., “Critical Parameter Values and Reconstruction Propertiesof Discrete Tomography: Application to Experimental FluidDynamics”, Fundamenta Informaticae, vol. 125, p. 285--312, 2013.

Technical Report (1.42 MB)

P. Swoboda and Schnörr, C., “Convex Variational Image Restoration with Histogram Priors”, SIAM J.~Imag.~Sci., vol. 6, pp. 1719-1735, 2013.

Technical Report (553.54 KB)

J. Yuan, Schnörr, C., and Steidl, G., “Convex Hodge Decomposition and Regularization of Image Flows”, J.~Math.~Imag.~Vision, vol. 33, pp. 169-177, 2009.

Technical Report (1003.75 KB)

J. Lellmann and Schnörr, C., “Continuous Multiclass Labeling Approaches and Algorithms”, SIAM J.~Imag.~Sci., vol. 4, pp. 1049-1096, 2011.

Technical Report (4.31 MB)

F. Rathke and Schnörr, C., “A Computational Approach to Log-Concave Density Estimation”, An. St. Univ. Ovidius Constanta, vol. 23, pp. 151-166, 2015.

Technical Report (1.07 MB)

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, International Journal of Computer Vision, pp. 1-30, 2015.

Technical Report (1.5 MB)

Technical Report (5.12 MB)

Technical Report (3.32 MB)

D. Breitenreicher, Lellmann, J., and Schnörr, C., “COAL: a generic modelling and prototyping framework for convex optimization problems of variational image analysis”, Optimization Methods and Software, vol. 28, pp. 1081-1094, 2013.

Technical Report (1.69 MB)

F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “A Class of Quasi-Variational Inequalities for Adaptive Image Denoising and Decomposition”, Computational Optimization and Applications (COAP), vol. 54 (2), pp. 371-398, 2013.

F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “A class of quasi-variational inequalities for adaptive image denoising and decomposition”, Computational Optimization and Applications, vol. 54, pp. 371-398, 2013.

Technical Report (748.66 KB)

S. Petra and Schnörr, C., “Average Case Recovery Analysis of Tomographic Compressive Sensing”, Linear Algebra and its Applications, vol. 441, pp. 168-198, 2014.

Technical Report (1.85 MB)

N. Gianniotis, Schnörr, C., Molkenthin, C., and Bora, S. S., “Approximate variational inference based on a finite sample of Gaussian latent variables”, Patt.~Anal.~Appl., 2015.

Technical Report (1.4 MB)

W. Hinterberger, Scherzer, O., Schnörr, C., and Weickert, J., “Analysis of Optical Flow Models in the Framework of Calculus of Variations”, Numer. Funct. Anal. Optimiz., vol. 23, pp. 69–89, 2002.

inproceedings

P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Partial Optimality by Pruning for MAP-inference with General GraphicalModels”, CVPR. Proceedings. pp. 1170-1177, 2014.

In Collection

M. Bergtholdt, Cremers, D., and Schnörr, C., “Variational Segmentation with Shape Priors”, Handbook of Mathematical Models in Computer Vision. Springer, pp. 147-160, 2005.

A. Vlasenko and Schnörr, C., “Variational Approaches for Model-Based PIV and Visual Fluid Analysis”, Imaging Measurement Methods for Flow Analysis, vol. 106. Springer, pp. 247-256, 2009.

Technical Report (3.39 MB)

M. Bergtholdt and Schnörr, C., “Shape Priors and Online Appearance Learning for Variational Segmentation and Object Recognition in Static Scenes”, Pattern Recognition, Proc. 27th DAGM Symposium, vol. 3663. Springer, pp. 342–350, 2005.

F. Rathke, Schmidt, S., and Schnörr, C., “Order preserving and shape prior constrained intra-retinal layer segmentation in optical coherence tomography”, Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), vol. 6893. Springer, pp. 370–377, 2011.

F. Becker, Petra, S., and Schnörr, C., “Optical Flow”, Handbook of Mathematical Methods in Imaging. Springer, 2014.

S. Petra, Schröder, A., and Schnörr, C., “3D Tomography from Few Projections in Experimental Fluid Mechanics”, Imaging Measurement Methods for Flow Analysis, vol. 106. Springer, pp. 63-72, 2009.

Technical Report (411.51 KB)

Conference Proceedings

E. Bodnariuc, Schiffner, M. F., Petra, S., and Schnörr, C., “Plane Wave Acoustic Superposition for Fast Ultrasound Imaging”, International Ultrasonics Symposium. 2016.

C. Schnörr and Jähne, B., “Pattern Recognition, 29th DAGM Symposium, Heidelberg, Germany, September 12-14”, vol. 4713. Springer, 2007.

F. A. Hamprecht, Schnörr, C., and Jähne, B., Eds., “Pattern Recognition – 29th DAGM Symposium”, LCNS, vol. 4713. Springer, 2007.

Conference Paper

B. Schmitzer and Schnörr, C., “Weakly Convex Coupling Continuous Cuts and Shape Priors”, in Scale Space and Variational Methods (SSVM 2011), 2012, pp. 423-434.

C. Gosch, Fundana, K., Heyden, A., and Schnörr, C., “View Point Tracking of Rigid Object Based on Shape Sub-Manifolds”, in Computer Vision -- ECCV 2008, 2008, vol. 5302, p. 251--263.

Technical Report (523.17 KB)

C. Gosch, Fundana, K., Heyden, A., and Schnörr, C., “View Point Tracking of Rigid Object Based on Shape Sub-Manifolds”, in Computer Vision – ECCV 2008, 2008, vol. 5302, pp. 251–263.

Publications

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