Schnörr,  (2020). Assignment Flows. Handbook of Variational Methods for Nonlinear Geometric Data. Springer. 235?260. https://www.springer.com/gp/book/9783030313500

 Zern, A, Zeilmann, A and Schnörr, C (2020). Assignment Flows for Data Labeling on Graphs: Convergence and Stability. preprint: arXiv. https://arxiv.org/abs/2002.11571

 Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2020). Geometric Numerical Integration of the Assignment Flow. Inverse Problems. 36 034004 (33pp)

 Desana, M and Schnörr, C (2020). Sum-Product Graphical Models. Machine Learning. 109 135?173

 Censor, Y, Petra, S and Schnörr, C (2020). Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case. J. Appl. Numer. Optimization (in press; arXiv:1911.05498). 2 15-62. http://jano.biemdas.com/archives/1060

 Zern, A, Zisler, M, Petra, S and Schnörr, C (2020). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. Journal of Mathematical Imaging and Vision. https://doi.org/10.1007/s10851-019-00935-7

 Schnörr,  (2019). Assignment Flows. Variational Methods for Nonlinear Geometric Data and Applications. Springer

 Savarino, F and Schnörr, C (2019). Continuous-Domain Assignment Flows. preprint: arXiv. https://arxiv.org/abs/1910.07287

 Rathke, F and Schnörr, C (2019). Fast Multivariate Log-Concave Density Estimation. Comp. Statistics & Data Analysis. 140 41?58

 Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2019). Geometric Numerical Integration of the Assignment Flow. Inverse Problems. https://doi.org/10.1088/1361-6420/ab2772

 Kostrykin, L, Schnörr, C and Rohr, K (2019). Globally Optimal Segmentation of Cell Nuclei in Fluoroscence Microscopy Images using Shape and Intensity Information. Medical Image Analysis. https://doi.org/10.1016/j.media.2019.101536

 Hühnerbein, R, Savarino, F, Petra, S and Schnörr, C (2019). Learning Adaptive Regularization for Image Labeling Using Geometric Assignment. preprint: arXiv. https://arxiv.org/abs/1910.09976

 Hühnerbein, R, Savarino, F, Petra, S and Schnörr, C (2019). Learning Adaptive Regularization for Image Labeling Using Geometric Assignment. Proc. SSVM. Springer

 Zisler, M, Zern, A, Petra, S and Schnörr, C (2019). Self-Assignment Flows for Unsupervised Data Labeling on Graphs. preprint: arXiv. https://arxiv.org/abs/1911.03472

 Desana, M and Schnörr, C (2019). Sum-Product Graphical Models. Machine Learning. https://doi.org/10.1007/s10994-019-05813-2

 Censor, Y, Petra, S and Schnörr, C (2019). Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case. preprint: arXiv. https://arxiv.org/abs/1911.05498

 Zern, A, Zisler, M, Petra, S and Schnörr, C (2019). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. preprint: arXiv. https://arxiv.org/abs/1904.10863

 Zisler, M, Zern, A, Petra, S and Schnörr, C (2019). Unsupervised Labeling by Geometric and Spatially Regularized Self-Assignment. Proc. SSVM. Springer

 Savarino, F and Schnörr, C (2019). A Variational Perspective on the Assignment Flow. Proc. SSVM. Springer

 Rathke, F and Schnörr, C (2018). Fast Multivariate Log-Concave Density Estimation. preprint: arXiv. https://arxiv.org/pdf/1805.07272.pdf

 Zern, A, Rohr, K and Schnörr, C (2018). Geometric Image Labeling with Global Convex Labeling Constraints. EMMCVPR. 10746 533?547

 Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2018). Geometric Numerical Integration of the Assignment Flow. preprint: arXiv. https://arxiv.org/abs/1810.06970

 Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM J. Imaging Science. 11 1317?1362. https://epubs.siam.org/doi/abs/10.1137/17M1150669

 Kostrykin, L, Schnörr, C and Rohr, K (2018). Segmentation of Cell Nuclei Using Intensity-Based Model Fitting and Sequential Convex Programming. Proc. ISBI

 Zern, A, Zisler, M, Aström, F, Petra, S and Schnörr, C (2018). Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment. GCPR

 Dalitz, R, Petra, S and Schnörr, C (2017). Compressed Motion Sensing. Proc. SSVM. Springer. 10302

 Aström, F and Schnörr, C (2017). A Geometric Approach for Color Image Regularization. Comp. Vision Image Understanding. 165 43?59. https://doi.org/10.1016/j.cviu.2017.10.013

 Zern, A, Rohr, K and Schnörr, C (2017). Geometric Image Labeling with Global Convex Labeling Constraints. Proc. EMMCVPR

 Zisler, M, Savarino, F, Petra, S and Schnörr, C (2017). Gradient Flows on a Riemannian Submanifold for Discrete Tomography. Proc. GCPR

 Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2017). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. http://arxiv.org/abs/1710.01493

 Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2017). Image Labeling by Assignment. J. Math. Imag. Vision. 58 211?238. Papers/Astroem2017.pdf

 Zisler, M, Aström, F, Petra, S and Schnörr, C (2017). Image Reconstruction by Multilabel Propagation. Proc. SSVM. Springer. 10302

 Bodnariuc, E, Petra, S, Schnörr, C and Voorneveld, J (2017). A Local Spatio-Temporal Approach to Plane Wave Ultrasound Particle Image Velocimetry. Proc. GCPR

 Rathke, F, Desana, M and Schnörr, C (2017). Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans. Proc. MICCAI

 Aström, F, Hühnerbein, R, Savarino, F, Recknagel, J and Schnörr, C (2017). MAP Image Labeling Using Wasserstein Messages and Geometric Assignment. Proc. SSVM. Springer. 10302

 Savarino, F, Hühnerbein, R, Aström, F, Recknagel, J and Schnörr, C (2017). Numerical Integration of Riemannian Gradient Flows for Image Labeling. Proc. SSVM. Springer. 10302

 Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2017). {Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. J. Math. Imag. Vision. 58 102?129

 Markowsky, P, Reith, S, Zuber, T E, König, R, Rohr, K and Schnörr, C (2017). Segmentation of cell structure using model-based set covering with iterative reweighting. Proc. ISBI

 Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). The Assignment Manifold: A Smooth Model for Image Labeling. Proc. 2nd Int. Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16; oral presentation; Grenander best paper award)

 Aström, F and Schnörr, C (2016). Double-Opponent Vectorial Total Variation. Proc. ECCV

 Desana, M and Schnörr, C (2016). Expectation Maximization for Sum-Product Networks as Exponential Family Mixture Models. http://arxiv.org/abs/1604.07243

 Aström, F and Schnörr, C (2016). A Geometric Approach to Color Image Regularization. https://arxiv.org/abs/1605.05977

 Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). A Geometric Approach to Image Labeling. Proc. ECCV

 Kappes, J, Speth, M, Reinelt, G and Schnörr, C (2016). Higher-order Segmentation via Multicuts. Comp. Vision Image Understanding. 143 104?119

 Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). Image Labeling by Assignment. http://arxiv.org/abs/1603.05285

 Censor, Y, Gibali, A, Lenzen, F and Schnörr, C (2016). The Implicit Convex Feasibility Problem and Its Application to Adaptive Image Denoising. J. Comp. Math. 34 608-623

 Kappes, J H, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2016). Multicuts and Perturb & MAP for Probabilistic Graph Clustering. J. Math. Imag. Vision. 56 221?237

 Bodnariuc, E, Petra, S, Poelma, C and Schnörr, C (2016). Parametric Dictionary-Based Velocimetry for Echo PIV. Proc. CGPR

 Swoboda, P, Shekhovtsov, A, Kappes, J H, Schnörr, C and Savchynskyy, B (2016). Partial Optimality by Pruning for MAP-Inference with General Graphical Models. IEEE Trans. Patt. Anal. Mach. Intell. 38 1370?1382

 Silvestri, F, Reinelt, G and Schnörr, C (2016). Symmetry-free SDP Relaxations for Affine Subspace Clustering. http://arxiv.org/abs/1607.07387

 Schmitzer, B and Schnörr, C (2015). Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes. J. Math. Imag. Vision. 52 436?458. http://link.springer.com/article/10.1007/s10851-014-0546-8

 Kappes, J, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2015). Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts. Proc. SSVM. Springer

 Didden, E - M, Thorarinsdottir, T L, Lenkoski, A and Schnörr, C (2015). Shape from Texture using Locally Scaled Point Processes. Image Anal. Stereol. 34 161-170

 Kappes, J H, Petra, S, Schnörr, C and Zisler, M (2015). TomoGC: Binary Tomography by Constrained Graph Cuts. Proc. GCPR

 Rathke, F, Schmidt, S and Schnörr, C (2014). Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization. Medical Image Analysis. 18 781-794

 Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J. Imag. Sci. 7 2139?2174

 Petra, S, Schnörr, C and Schröder, A (2012). Critical Parameter Values and Reconstruction Properties of Discrete Tomography: Application to Experimental Fluid Dynamics. http://arxiv.org/abs/1209.4316

 Lellmann, J and Schnörr, C (2011). Continuous Multiclass Labeling Approaches and Algorithms. CoRR. abs/1102.5448. http://arxiv.org/abs/1102.5448

 Nicola, A, Petra, S, Popa, C and Schnörr, C (2011). A general extending and constraining procedure for linear iterative methods. Int. J. Comp. Math. http://dx.doi.org/10.1080/00207160.2011.634002

 Lellmann, J and Schnörr, C (2011). Regularizers for Vector-Valued Data and Labeling Problems in Image Processing. Control Systems and Computers. 2 43?54

 Savchynskyy, B, Kappes, J H, Schmidt, S and Schnörr, C (2011). A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)

 Lellmann, J and Schnörr, C (2010). Continuous Multiclass Labeling Approaches And Algorithms. Univ. of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/10460/

 Lellmann, J, Breitenreicher, D and Schnörr, C (2010). Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6312 494?505

 Kappes, J H, Schmidt, S and Schnörr, C (2010). MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation. European Conference on Computer Vision (ECCV). Springer Berlin / Heidelberg. 6313 735?747

 Vlasenko, A and Schnörr, C (2010). Physically Consistent and Efficient Variational Denoising of Image Fluid Flow Estimates. IEEE Trans. Image Proc. 19 586-595

 Heitz, D, Mémin, E and Schnörr, C (2010). Variational fluid flow measurements from image sequences: synopsis and perspectives. Exp. Fluids. 48 369-393

 Nicola, A, Petra, S, Popa, C and Schnörr, C (2009). On A General Extending And Constraining Procedure For Linear Iterative Methods. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9761

 Lauer, F and Schnörr, C (2009). Spectral Clustering of Linear Subspaces for Motion Segmentation. Proc. IEEE Int. Conf. Computer Vision (ICCV'09). Kyoto, Japan

 Petra, S and Schnörr, C (2009). Tomopiv Meets Compressed Sensing. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/9760

 Petra, S and Schnörr, C (2009). TomoPIV meets Compressed Sensing. Pure Math. Appl. 20 49 ? 76. http://www.mat.unisi.it/newsito/puma/public_html/contents.php

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

 Petra, S, Popa, C and Schnörr, C (2008). Enhancing Sparsity by Constraining Strategies: Constrained SIRT versus Spectral Projected Gradient Methods. Proc. 7th Workshop on Modelling of Environmental and Life Sciences Problems (WMM 08). Ed Acad Romane, Bucuresti, Constanta, Romania

 Petra, S, Popa, C and Schnörr, C (2008). Enhancing Sparsity by Constraining Strategies: Constrained SIRT versus Spectral Projected Gradient Methods. Proc. 7th Workshop on Modelling of Environmental and Life Sciences Problems (WMM 08). Bucharest, Romania

 Kappes, J H and Schnörr, C (2008). MAP-Inference for Highly-Connected Graphs with DC-Programming. Pattern Recognition ? 30th DAGM Symposium. Springer Verlag. 5096 1?10

 Munder, S, Schnörr, C and Gavrila, D M (2008). Pedestrian Detection and Tracking Using a Mixture of View-Based Shape-Texture Models. IEEE Trans. Intell. Transp. Systems. 9 333-343

 Vlasenko, A and Schnörr, C (2008). Physically Consistent Variational Denoising of Image Fluid Flow Estimates. Pattern Recognition ? 30th DAGM Symposium. Springer Verlag. 5096 406?415

 Petra, S, Schröder, A, Wieneke, B and Schnörr, C (2008). On Sparsity Maximization in Tomographic Particle Image Reconstruction. Pattern Recognition ? 30th DAGM Symposium. Springer Verlag. 5096 294?303

 Schellewald, C, Roth, S and Schnörr, C (2007). Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views. Image Vision Comp. 25 1301?1314

 Karim, R, Bergtholdt, M, Kappes, J H and Schnörr, C (2007). Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification. Pattern Recognition ? 29th DAGM Symposium. Springer. 4713 395-404

 Welk, M, Weickert, J, Becker, F, Schnörr, C, Feddern, C and Burgeth, B (2007). Median and related local filters for tensor-valued images. Signal Processing. 87 291-308

 Ruhnau, P and Schnörr, C (2007). Optical Stokes Flow Estimation: An Imaging-Based Control Approach. Exp. in Fluids. 42 61?78

 Schnörr,  (2007). Signal and Image Approximation with Level-Set Constraints. Computing. 81 137-160

 Yuan, J, Schnörr, C and Steidl, G (2007). Simultaneous Optical Flow Estimation and Decomposition. SIAM J. Scientific Computing. 29 2283-2304

 Schmidt, S, Kappes, J H, Bergtholdt, M, Pekar, V, Dries, S, Bystrov, D and Schnörr, C (2007). Spine Detection and Labeling Using a Parts-Based Graphical Model. Proc. 20th International Conference on Information Processing in Medical Imaging (IPMI 2007). Springer. 4584 122-133

 Petra, S, Schnörr, C, Schröder, A and Wieneke, B (2007). Tomographic Image Reconstruction in Experimental Fluid Dynamics: Synopsis and Problems. Proc. 6th Workshop on Modelling of Environmental and Life Sciences Problems (WMM 07). Ed Acad Romane, Bucuresti, Constanta, Romania

 Ruhnau, P, Stahl, A and Schnörr, C (2007). Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization. Measurement Science and Technology. 18 755-763

 Schnörr, C, Schüle, T and Weber, S (2007). Variational Reconstruction with DC-Programming. Advances in Discrete Tomography and Its Applications. Birkhäuser, Boston

 Heiler, M and Schnörr, C (2006). Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming. J. Mach. Learning Res. 7 1385?1407. http://www.cvgpr.uni-mannheim.de/Publications

 Ruhnau, P, Stahl, A and Schnörr, C (2006). On-Line Variational Estimation of Dynamical Fluid Flows with Physics-Based Spatio-Temporal Regularization. Proc. DAGM 2006. Springer. 375-388 375-388

 Schüle, T, Weber, S and Schnörr, C (2005). Adaptive Reconstruction of Discrete-Valued Objects from few Projections. Electr. Notes in Discr. Math. 20 365-384

 Weber, S, Schnörr, C, Schüle, T and Hornegger, J (2005). Binary Tomography by Iterating Linear Programs. Geometric Properties from Incomplete Data. Springer

 Neumann, J, Schnörr, C and Steidl, G (2005). Combined SVM-based Feature Selection and Classification. Machine Learning. 61 129-150

 Yuan, J, Ruhnau, P, Mémin, E and Schnörr, C (2005). Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation. Scale-Space 2005. Springer. 3459 267?278

 Schüle, T, Schnörr, C, Weber, S and Hornegger, J (2005). Discrete Tomography By Convex-Concave Regularization and D.C. Programming. Discr. Appl. Math. 151 229-243

 Kohlberger, T, Schnörr, C, Bruhn, A and Weickert, J (2005). Domain decomposition for variational optical flow computation. IEEE Trans. Image Proc. 14 1125-1137

 Neumann, J, Schnörr, C and Steidl, G (2005). Efficient Wavelet Adaption for Hybrid Wavelet-Large Margin Classifiers. Pattern Recognition. 38 1815-1830

 Heiler, M and Schnörr, C (2005). Learning Sparse Image Codes by Convex Programming. Proc. Tenth IEEE Int. Conf. Computer Vision (ICCV'05). Beijing, China. 1667-1674

 Heiler, M and Schnörr, C (2005). Natural Image Statistics for Natural Image Segmentation. Int. J. Comp. Vision. 63 5?19

 Weber, S, Schüle, T and Schnörr, C (2005). Prior Learning and Convex-Concave Regularization of Binary Tomography. Electr. Notes in Discr. Math. 20 313-327

 Schellewald, C and Schnörr, C (2005). Probabilistic Subgraph Matching Based on Convex Relaxation. Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 171-186

 Heiler, M and Schnörr, C (2005). Reverse-Convex Programming for Sparse Image Codes. Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 600-616

 Heiler, M, Keuchel, J and Schnörr, C (2005). Semidefinite Clustering for Image Segmentation with A-priori Knowledge. Pattern Recognition, Proc. 27th DAGM Symposium. Springer. 3663 309?317

 Ruhnau, P, Gütter, C, Putze, T and Schnörr, C (2005). A variational approach for particle tracking velocimetry. Meas. Science and Techn. 16 1449-1458

 (2005). Variational, Geometric and Level Sets in Computer Vision (VLSM'05). lncs. Springer, Beijing, China. 3752

 Ruhnau, P, Kohlberger, T, Nobach, H and Schnörr, C (2005). Variational Optical Flow Estimation for Particle Image Velocimetry. Experiments in Fluids. 38 21?32

 Giebel, J, Gavrila, D M and Schnörr, C (2004). A Bayesian Framework for Multi-cue 3D Object Tracking. Computer Vision ? ECCV 2004. Springer. 3024 241-252

 Weber, S, Schüle, T, Hornegger, J and Schnörr, C (2004). Binary Tomography by Iterating Linear Programs from Noisy Projections. Combinatorial Image Analysis, Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'04). Springer Verlag. 3322 38?51

 Yuan, J, Schnörr, C, Kohlberger, T and Ruhnau, P (2004). Convex Set-Based Estimation of Image Flows. ICPR 2004 ? 17th Int. Conf. on Pattern Recognition. IEEE, Cambridge, UK. 1 124-127

 Keuchel, J, Heiler, M and Schnörr, C (2004). Hierarchical Image Segmentation based on Semidefinite Programming. Pattern Recognition, Proc. 26th DAGM Symposium. Springer. 3175 120-128

 Weber, S, Schüle, T, Schnörr, C and Hornegger, J (2004). A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections. Methods of Information in Medicine. 43 320?326

 Kohlberger, T, Schnörr, C, Bruhn, A and Weickert, J (2004). Parallel Variational Motion Estimation by Domain Decomposition and Cluster Computing. Computer Vision ? ECCV 2004. Springer. 3024 205-216

 Neumann, J, Schnörr, C and Steidl, G (2004). SVM-based Feature Selection by Direct Objective Minimisation. Pattern Recognition, Proc. 26th DAGM Symposium. Springer. 3175 212-219

 Ruhnau, P, Kohlberger, T, Nobach, H and Schnörr, C (2004). Variational Optical Flow Estimation for Particle Image Velocimetry. Proc. Lasermethoden in der Strömungsmeßtechnik. Deutsche Gesellschaft für Laser-Anemometrie GALA e.V., Karlsruhe

 Keuchel, J, Schnörr, C, Schellewald, C and Cremers, D (2003). Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming. 25 1364?1379

 Schüle, T, Schnörr, C, Weber, S and Hornegger, J (2003). Discrete Tomography By Convex-Concave Regularization And D.c. Programming. Dept. Math. and Comp. Science, University of Mannheim, Germany

 Kohlberger, T, Schnörr, C, Bruhn, A and Weickert, J (2003). Domain Decomposition for Parallel Variational Optical Flow Computation. Pattern Recognition, Proc. 25th DAGM Symposium. Springer. 2781 196?203

 Kohlberger, T, Schnörr, C, Bruhn, A and Weickert, J (2003). Domain Decomposition For Variational Optical Flow Computation. Dept. Math. and Comp. Science, University of Mannheim, Germany

 Neumann, J, Schnörr, C and Steidl, G (2003). Effectively Finding The Optimal Wavelet For Hybrid Wavelet - Large Margin Signal Classification. Dept. Math. and Comp. Science, University of Mannheim, Germany

 Neumann, J, Schnörr, C and Steidl, G (2003). Feasible Adaption Criteria for Hybrid Wavelet ? Large Margin Classifiers. Proc. Computer Analysis of Images and Patterns (CAIP'03). Springer. 2756 588?595

 Weber, S, Schüle, T, Schnörr, C and Hornegger, J (2003). A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections. Bildverarbeitung für die Medizin 2003. Springer Verlag. 41?45

 Weber, S, Schnörr, C and Hornegger, J (2003). A Linear Programming Relaxation for Binary Tomography with Smoothness Priors. Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'03). Palermo, Italy

 Heiler, M and Schnörr, C (2003). Natural Statistics for Natural Image Segmentation. Proc. IEEE Int. Conf. Computer Vision (ICCV 2003). Nice, France. 1259-1266

 Schellewald, C and Schnörr, C (2003). Subgraph Matching with Semidefinite Programming. Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'03). Palermo, Italy

 Kohlberger, T, Mémin, E and Schnörr, C (2003). Variational Dense Motion Estimation Using the Helmholtz Decomposition. Scale Space Methods in Computer Vision. Springer. 2695 432?448

 Schellewald, C, Roth, S and Schnörr, C (2002). Performance Evaluation Of A Convex Relaxation Approach To The Quadratic Assignment Of Relational Object Views. Dept. Math. and Comp. Science, University of Mannheim, Germany

 Keuchel, J, Schnörr, C, Schellewald, C and Cremers, D (2002). Unsupervised Image Partitioning with Semidefinite Programming. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 141?149

 Wiehler, K, Heers, J, Schnörr, C, Stiehl, H ?S and Grigat, R ?R (2001). A 1D analog VLSI implementation for non-linear real-time signal preprocessing. Real?Time Imaging. 7 127?142

 Schellewald, C, Roth, S and Schnörr, C (2001). Application Of Convex Optimization Techniques To The Relational Matching Of Object Views. Dept. Math. and Comp. Science, University of Mannheim, Germany

 Keuchel, J, Schellewald, C, Cremers, D and Schnörr, C (2001). Convex Relaxations for Binary Image Partitioning and Perceptual Grouping. Mustererkennung 2001. Springer, Munich, Germany. 2191 353?360

 Heiler, M, Cremers, D and Schnörr, C (2001). Efficient Feature Subset Selection For Support Vector Machines. Dept. Math. and Comp. Science, University of Mannheim, Germany

 Schellewald, C, Roth, S and Schnörr, C (2001). Evaluation of Convex Optimization Techniques for the Weighted Graph?Matching Problem in Computer Vision. Mustererkennung 2001. Springer, Munich, Germany. 2191 361?368

 Weickert, J, Heers, J, Schnörr, C, Zuiderveld, K ?J, Scherzer, O and Stiehl, H ?S (2001). Fast parallel algorithms for a broad class of nonlinear variational diffusion approaches. Real?Time Imaging. 7 31?45

 Heers, J, Schnörr, C and Stiehl, H S (2001). Globally?Convergent Iterative Numerical Schemes for Non?Linear Variational Image Smoothing and Segmentation on a Multi?Processor Machine. IEEE Trans. Image Proc. 10 852?864

 Schellewald, C, Keuchel, J and Schnörr, C (2001). Image labeling and grouping by minimizing linear functionals over cones. Proc. Third Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'01). Springer, INRIA, Sophia Antipolis, France. 2134 267?282

 Weickert, J and Schnörr, C (2001). A Theoretical Framework for Convex Regularizers in PDE?Based Computation of Image Motion. Int. J. Computer Vision. 45 245?264

 Weickert, J and Schnörr, C (2001). Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint. J. Math. Imaging and Vision. 14 245?255

 Wulf, M, Stiehl, H S and Schnörr, C (2000). On the computational rôle of the primate retina. Proc. 2nd ICSC Symposium on Neural Computation (NC 2000). Berlin, Germany

 (2000). Künstliche Intelligenz: Special Issue on Medical Computer Vision. 3

 Weickert, J and Schnörr, C (2000). PDE?Based Preprocessing of Medical Images. Künstliche Intelligenz. 3 5?10

 Schnörr,  (2000). Variational Adaptive Smoothing and Segmentation. Computer Vision and Applications: A Guide for Students and Practitioners. Academic Press, San Diego. 459?482

 Schnörr, C and Weickert, J (2000). Variational Image Motion Computation: Theoretical Framework, Problems and Perspectives. Mustererkennung 2000. Springer, Kiel, Germany

 Heers, J, Schnörr, C and Stiehl, H S (1999). 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

 Wulf, M, Stiehl, H S and Schnörr, C (1999). A model of spatiotemporal receptive fields in the primate retina. Proc. 1st Göttingen Conf. German Neurosci. Soc.. II

 Wulf, M, Stiehl, H S and Schnörr, C (1999). Modeling spatiotemporal receptive fields in the primate retina. Proc. Cognitive Neurosci. Conf. Hanse?Wissenschaftskolleg, Bremen, Germany

 Peckar, W, Schnörr, C, Rohr, K and Stiehl, H ?S (1999). Parameter-Free Elastic Deformation Approach for 2D and 3D Registration Using Prescribed Displacements. J. Math. Imaging and Vision. 10 143?162

 Weickert, J and Schnörr, C (1999). Räumlich?zeitliche Berechnung des optischen Flusses mit nichtlinearen flussabhängigen Glattheitstermen. Mustererkennung 1999. Springer. 317?324

 Schnörr,  (1999). Variational Methods for Adaptive Image Smoothing and Segmentation. Handbook on Computer Vision and Applications: Signal Processing and Pattern Recognition. Academic Press, San Diego. 2 451?484

 Heers, J, Schnörr, C and Stiehl, H S (1998). A class of parallel algorithms for nonlinear variational image segmentation. Proc. Noblesse Workshop on Non?Linear Model Based Image Analysis (NMBIA'98). Glasgow, Scotland

 Wiehler, K, Grigat, R ?R, Heers, J, Schnörr, C and Stiehl, H S (1998). Dynamic Circular Cellular Networks for Adaptive Smoothing of Multi?Dimensional Signals. Proc. 5th IEEE Int. Workshop on Cellular Neural Networks and their Applications. London

 Heers, J, Schnörr, C and Stiehl, H ?S (1998). Investigation of Parallel and Globally Convergent Iterative Schemes for Nonlinear Variational Image Smoothing and Segmentation. Proc. IEEE Int. Conf. Image Proc. Chicago

 Peckar, W, Schnörr, C, Rohr, K, Stiehl, H ?S and Spetzger, U (1998). Linear and Incremental Estimation of Elastic Deformations in Medical Registration Using Prescribed Displacements. Machine Graphics & Vision. 7 807?829

 Peckar, W, Schnörr, C, Rohr, K and Stiehl, H S (1998). Non-Rigid Image Registration Using a Parameter-Free Elastic Model. 9th British Machine Vision Conference (BMVC`98). Southampton/UK. 134?143

 Heers, J, Schnörr, C and Stiehl, H ?S (1998). Parallele und global konvergente iterative Minimierung nichtlinearer Variationsansätze zur adaptiven Glättung und Segmentation von Bildern. Mustererkennung 1998. Springer, Heidelberg

 Wiehler, K, Grigat, R ?R, Heers, J, Schnörr, C and Stiehl, H ?S (1998). Real?Time Adaptive Smoothing with a 1D Nonlinear Relaxation Network in Analogue VLSI Technology. Mustererkennung 1998. Springer, Heidelberg

 Schnörr,  (1998). A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction. J. of Math. Imag. and Vision. 8 271?292

 Schnörr,  (1998). Variational approaches to Image Segmentation and Feature Extraction. University of Hamburg, Comp. Sci. Dept., Hamburg, Germany

 Gerloff, S, Hagemann, A, Schnörr, C, Tieck, S, Stiehl, H S, Dombrowski, R, Dreyer, M and Wiesendanger, R (1997). Semi?Automated Analysis of SXM Images. Proc. 9th Int. Conf. on Scanning Tunneling Microscopy/Spectroscopy and Related Techniques (STM'97). Hamburg, Germany

 Peckar, W, Schnörr, C, Rohr, K and Stiehl, H S (1997). Two-Step Parameter-Free Elastic Image Registration with Prescribed Point Displacements. Proc. 9th Int. Conf. on Image Analysis and Processing (ICIAP'97). Florence, Italy

 Schnörr,  (1996). Convex Variational Segmentation of Multi-Channel Images. Proc. 12th Int. Conf. on Analysis and Optimization of Systems: Images, Wavelets and PDE's. Springer-Verlag, Paris. 219

 Schnörr, C, Stiehl, H - S and Grigat, R - R (1996). On Globally Asymptotically Stable Continuous-Time CNNs for Adaptive Smoothing of Multidimensional Signals. Proc. 4th IEEE Int. Workshop on Cellular Neural Networks and their Applications. Seville, Spain

 Schnörr,  (1996). Repräsentation von Bilddaten mit einem konvexen Variationsansatz. Mustererkennung 1996. Springer-Verlag, Berlin, Heidelberg. 21?28

 Schnörr,  (1996). Representation Of Images By A Convex Variational Diffusion Approach. FB Informatik, Universität Hamburg

 Schnörr, C, Sprengel, R and Neumann, B (1996). A Variational Approach to the Design of Early Vision Algorithms. Computing Suppl. 11 149-165

 Schnörr, C and Peckar, W (1995). Motion-Based Identification of Deformable Templates. Proc. 6th Int. Conf. on Computer Analysis of Images and Patterns (CAIP '95). Springer Verlag, Prague, Czech Republic. 970 122-129

 Schnörr,  (1994). Bewegungssegmentation von Bildfolgen durch die Minimierung konvexer nicht-quadratischer Funktionale. Mustererkennung 1994. Technische Universität Wien. 5 178?185

 Heikkonen, J, Koikkalainen, P and Schnörr, C (1994). Building Trajectories via Selforganization from Spatiotemporal Features. 12th Int. Conf. on Pattern Recognition. Jerusalem, Israel

 Sprengel, R, Schnörr, C and Neumann, B (1994). Detection of Visual Data Transitions in Nonlinear Parameter Space. Mustererkennung 1994. Technische Universität Wien. 5 315?323

 Schnörr, C and Sprengel, R (1994). A Nonlinear Regularization Approach to Early Vision. Biol. Cybernetics. 72 141?149

 Schnörr,  (1994). Segmentation of Visual Motion by Minimizing Convex Non-Quadratic Functionals. 12th Int. Conf. on Pattern Recognition. Jerusalem, Israel

 Schnörr,  (1994). Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals. 4 189?198

 Schnörr, C, Niemann, H and Kopecz, J (1993). Architekturkonzepte zur Bildauswertung. Grundlagen und Anwendungen der Künstlichen Intelligenz, 17. Fachtagung für Künstliche Intelligenz. Springer-Verlag, Berlin. 268?274

 Schnörr,  (1993). On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow. pami. 15 1074?1079

 Sprengel, R and Schnörr, C (1993). Nichtlineare Diffusion zur Integration visueller Daten - Anwendung auf Kernspintomogramme. Mustererkennung 1993, 15. DAGM-Symposium. Springer Verlag. 134?141

 Schnörr,  (1992). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. ijcv. 8 153?165

 Schnörr, C and Neumann, B (1992). Ein Ansatz zur effizienten und eindeutigen Rekonstruktion stückweise glatter Funktionen. Mustererkennung 1992, 14. DAGM-Symposium. Springer-Verlag, Dresden. 411?416

 Schnörr,  (1991). Determining Optical Flow for Irregular Domains by Minimizing Quadratic Functionals of a Certain Class. ijcv. 6 25?38

 Schnörr,  (1991). Funktionalanalytische Methoden zur Bestimmung von Bewegungsinformation aus TV-Bildfolgen. Fakultät für Informatik, Universität Karlsruhe (TH)

 Bister, D, Rohr, K and Schnörr, C (1990). Automatische Bestimmung der Trajektorien von sich bewegenden Objekten aus einer Grauwertbildfolge. Mustererkennung 1990, 12. DAGM-Symposium. Springer-Verlag, Oberkochen-Aalen. 254 44?51

 Schnörr,  (1990). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. Proc. British Machine Vision Conference. Oxford/UK. 109?114

 Schnörr,  (1989). Zur Schätzung von Geschwindigkeitsvektorfeldern in Bildfolgen mit einer richtungsabhängigen Glattheitsforderung. Mustererkennung 1989, 11. DAGM-Symposium. Springer-Verlag, Hamburg. 219 294?301