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C. Schnörr, Assignment Flows, Handbook of Variational Methods for Nonlinear Geometric Data. Springer, p. 235—260, 2020.
C. Schnörr, Assignment Flows, Variational Methods for Nonlinear Geometric Data and Applications. Springer, 2019.
C. Schnörr, Zur Schätzung von Geschwindigkeitsvektorfeldern in Bildfolgen mit einer richtungsabhängigen Glattheitsforderung, in Mustererkennung 1989, 11. DAGM-Symposium, Hamburg, 1989, vol. 219, pp. 294–301.
C. Schnörr, Repräsentation von Bilddaten mit einem konvexen Variationsansatz, in Mustererkennung 1996, Berlin, Heidelberg, 1996, pp. 21–28.
C. Schnörr, Variational Adaptive Smoothing and Segmentation, in Computer Vision and Applications: A Guide for Students and Practitioners, San Diego, 2000, pp. 459–482.
C. Schnörr, Variational Methods for Adaptive Image Smoothing and Segmentation, in Handbook on Computer Vision and Applications: Signal Processing and Pattern Recognition, San Diego, 1999, vol. 2, pp. 451–484.
C. Schnörr, Bewegungssegmentation von Bildfolgen durch die Minimierung konvexer nicht-quadratischer Funktionale, in Mustererkennung 1994, 1994, vol. 5, pp. 178–185.
C. Schnörr, Signal and Image Approximation with Level-Set Constraints, Computing, vol. 81, pp. 137-160, 2007.
C. Schnörr, Variational approaches to Image Segmentation and Feature Extraction. University of Hamburg, Comp. Sci. Dept., Hamburg, Germany, 1998.
C. Schnörr, A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction, J. of Math. Imag. and Vision, vol. 8, pp. 271–292, 1998.
C. Schnörr, Representation of Images by a Convex Variational Diffusion Approach, FB Informatik, Universität Hamburg, FBI-HH-M-256/96, 1996.
C. Schnörr, Segmentation of Visual Motion by Minimizing Convex Non-Quadratic Functionals, in 12th Int. Conf. on Pattern Recognition, Jerusalem, Israel, 1994.
C. Schnörr, Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals, vol. 4, pp. 189–198, 1994.
C. Schnörr, On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow, pami, vol. 15, pp. 1074–1079, 1993.
C. Schnörr, Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization, ijcv, vol. 8, pp. 153–165, 1992.
C. Schnörr, Funktionalanalytische Methoden zur Bestimmung von Bewegungsinformation aus TV-Bildfolgen. Fakultät für Informatik, Universität Karlsruhe (TH), 1991.
C. Schnörr, Determining Optical Flow for Irregular Domains by Minimizing Quadratic Functionals of a Certain Class, ijcv, vol. 6, pp. 25–38, 1991.
C. Schnörr, Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization, in Proc. British Machine Vision Conference, Oxford/UK, 1990, pp. 109–114.
C. Schnörr and Neumann, B., Ein Ansatz zur effizienten und eindeutigen Rekonstruktion stückweise glatter Funktionen, in Mustererkennung 1992, 14. DAGM-Symposium, Dresden, 1992, pp. 411–416.
C. Schnörr, Niemann, H., and Kopecz, J., Architekturkonzepte zur Bildauswertung, in Grundlagen und Anwendungen der Künstlichen Intelligenz, 17. Fachtagung für Künstliche Intelligenz, Berlin, 1993, pp. 268–274.
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.
C. Schnörr, Schüle, T., and Weber, S., Variational Reconstruction with DC-Programming, Advances in Discrete Tomography and Its Applications. Birkhäuser, Boston, 2007.
C. Schnörr and Sprengel, R., A Nonlinear Regularization Approach to Early Vision, Biol. Cybernetics, vol. 72, pp. 141–149, 1994.
C. Schnörr, Sprengel, R., and Neumann, B., A Variational Approach to the Design of Early Vision Algorithms, Computing Suppl., vol. 11, pp. 149-165, 1996.
C. Schnörr, Stiehl, H. - S., and Grigat, R. - R., On Globally Asymptotically Stable Continuous-Time CNNs for Adaptive Smoothing of Multidimensional Signals, in Proc. 4th IEEE Int. Workshop on Cellular Neural Networks and their Applications, Seville, Spain, 1996.
C. Schnörr and Weickert, J., Variational Image Motion Computation: Theoretical Framework, Problems and Perspectives, in Mustererkennung 2000, Kiel, Germany, 2000.
C. Schnörr, Convex Variational Segmentation of Multi-Channel Images, in Proc. 12th Int. Conf. on Analysis and Optimization of Systems: Images, Wavelets and PDE's, Paris, 1996, vol. 219.
C. Schnörr, Ed., Künstliche Intelligenz: Special Issue on Medical Computer Vision, vol. 3. 2000.