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J. Heers, Schnörr, C., and Stiehl, H. –S., “Parallele und global konvergente iterative Minimierung nichtlinearer Variationsansätze zur adaptiven Glättung und Segmentation von Bildern”, in Mustererkennung 1998, Heidelberg, 1998.
T. Kohlberger, Schnörr, C., Bruhn, A., and Weickert, J., “Parallel Variational Motion Estimation by Domain Decomposition and Cluster Computing”, in Computer Vision – ECCV 2004, 2004, vol. 3024, pp. 205-216.
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P. Ruhnau and Schnörr, C., “Optical Stokes Flow Estimation: An Imaging-Based Control Approach”, Exp. in Fluids, vol. 42, pp. 61–78, 2007.
P. Ruhnau, Stahl, A., and Schnörr, C., “On-Line Variational Estimation of Dynamical Fluid Flows with Physics-Based Spatio-Temporal Regularization”, in Proc. DAGM 2006, 2006, vol. 375-388, pp. 375-388.
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F. Savarino, Hühnerbein, R., Aström, F., Recknagel, J., and Schnörr, C., “Numerical Integration of Riemannian Gradient Flows for Image Labeling”, in Proc. SSVM, 2017, vol. 10302.
W. Peckar, Schnörr, C., Rohr, K., and Stiehl, H. S., “Non-Rigid Image Registration Using a Parameter-Free Elastic Model”, in 9th British Machine Vision Conference (BMVC`98), Southampton/UK, 1998, pp. 134–143.
C. Schnörr and Sprengel, R., “A Nonlinear Regularization Approach to Early Vision”, Biol. Cybernetics, vol. 72, pp. 141–149, 1994.
R. Sprengel and Schnörr, C., “Nichtlineare Diffusion zur Integration visueller Daten - Anwendung auf Kernspintomogramme”, in Mustererkennung 1993, 15. DAGM-Symposium, 1993, pp. 134–141.
M. Heiler and Schnörr, C., “Natural Statistics for Natural Image Segmentation”, in Proc. IEEE Int. Conf. Computer Vision (ICCV 2003), Nice, France, 2003, pp. 1259-1266.
M. Heiler and Schnörr, C., “Natural Image Statistics for Natural Image Segmentation”, Int. J. Comp. Vision, vol. 63, pp. 5–19, 2005.
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J. H. Kappes, Swoboda, P., Savchynskyy, B., Hazan, T., and Schnörr, C., “Multicuts and Perturb & MAP for Probabilistic Graph Clustering”, J. Math. Imag. Vision, vol. 56, pp. 221–237, 2016.
J. H. Kappes, Schmidt, S., and Schnörr, C., “MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation”, in European Conference on Computer Vision (ECCV), 2010, vol. 6313, pp. 735–747.
C. Schnörr and Peckar, W., “Motion-Based Identification of Deformable Templates”, in Proc. 6th Int. Conf. on Computer Analysis of Images and Patterns (CAIP '95), Prague, Czech Republic, 1995, vol. 970, pp. 122-129.
M. Wulf, Stiehl, H. S., and Schnörr, C., “Modeling spatiotemporal receptive fields in the primate retina”, in Proc. Cognitive Neurosci. Conf., Bremen, Germany, 1999.
M. Wulf, Stiehl, H. S., and Schnörr, C., “A model of spatiotemporal receptive fields in the primate retina”, in Proc. 1st Göttingen Conf. German Neurosci. Soc., 1999, vol. II.
M. Welk, Weickert, J., Becker, F., Schnörr, C., Feddern, C., and Burgeth, B., “Median and related local filters for tensor-valued images”, Signal Processing, vol. 87, pp. 291-308, 2007.
J. H. Kappes and Schnörr, C., “MAP-Inference for Highly-Connected Graphs with DC-Programming”, in Pattern Recognition – 30th DAGM Symposium, 2008, vol. 5096, pp. 1–10.
F. Aström, Hühnerbein, R., Savarino, F., Recknagel, J., and Schnörr, C., “MAP Image Labeling Using Wasserstein Messages and Geometric Assignment”, in Proc. SSVM, 2017, vol. 10302.
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F. Rathke, Desana, M., and Schnörr, C., “Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans”, in Proc. MICCAI, 2017.
E. Bodnariuc, Petra, S., Schnörr, C., and Voorneveld, J., “A Local Spatio-Temporal Approach to Plane Wave Ultrasound Particle Image Velocimetry”, in Proc. GCPR, 2017.
S. Weber, Schnörr, C., and Hornegger, J., “A Linear Programming Relaxation for Binary Tomography with Smoothness Priors”, in Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'03), Palermo, Italy, 2003.
S. Weber, Schüle, T., Schnörr, C., and Hornegger, J., “A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections”, Methods of Information in Medicine, vol. 43, pp. 320–326, 2004.
S. Weber, Schüle, T., Schnörr, C., and Hornegger, J., “A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections”, in Bildverarbeitung für die Medizin 2003, 2003, pp. 41–45.
W. Peckar, Schnörr, C., Rohr, K., Stiehl, H. –S., and Spetzger, U., “Linear and Incremental Estimation of Elastic Deformations in Medical Registration Using Prescribed Displacements”, Machine Graphics & Vision, vol. 7, pp. 807–829, 1998.
M. Heiler and Schnörr, C., “Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming”, J. Mach. Learning Res., vol. 7, pp. 1385–1407, 2006.
M. Heiler and Schnörr, C., “Learning Sparse Image Codes by Convex Programming”, in Proc. Tenth IEEE Int. Conf. Computer Vision (ICCV'05), Beijing, China, 2005, pp. 1667-1674.
R. Hühnerbein, Savarino, F., Petra, S., and Schnörr, C., “Learning Adaptive Regularization for Image Labeling Using Geometric Assignment”, preprint: arXiv, 2019.
R. Hühnerbein, Savarino, F., Petra, S., and Schnörr, C., “Learning Adaptive Regularization for Image Labeling Using Geometric Assignment”, in Proc. SSVM, 2019.
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C. Schnörr, Ed., “Künstliche Intelligenz: Special Issue on Medical Computer Vision”, vol. 3. 2000.
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J. Heers, Schnörr, C., and Stiehl, H. –S., “Investigation of Parallel and Globally Convergent Iterative Schemes for Nonlinear Variational Image Smoothing and Segmentation”, in Proc. IEEE Int. Conf. Image Proc., Chicago, 1998.
J. Heers, Schnörr, C., and Stiehl, H. S., “Investigating a class of iterative schemes and their parallel implementation for nonlinear variational image smoothing and segmentation”, Comp. Sci. Dept., AB KOGS, University of Hamburg, Germany, 283/99, 1999.
Y. Censor, Gibali, A., Lenzen, F., and Schnörr, C., “The Implicit Convex Feasibility Problem and Its Application to Adaptive Image Denoising”, J. Comp. Math., vol. 34, pp. 608-623, 2016.
M. Zisler, Aström, F., Petra, S., and Schnörr, C., “Image Reconstruction by Multilabel Propagation”, in Proc. SSVM, 2017, vol. 10302.
F. Aström, Petra, S., Schmitzer, B., and Schnörr, C., “Image Labeling by Assignment”, J. Math. Imag. Vision, vol. 58, pp. 211–238, 2017.
F. Aström, Petra, S., Schmitzer, B., and Schnörr, C., “Image Labeling by Assignment”. 2016.

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