Publications

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Journal Article
Kappes, J H, 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 (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. International Journal of Computer Vision. 1-30PDF icon Technical Report (1.5 MB)
Kappes, J H, 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 (2014). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. CoRR. http://arxiv.org/abs/1404.0533
Kappes, J H, 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 (2014). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. CoRR. abs/1404.0533. http://hci.iwr.uni-heidelberg.de/opengm2/PDF icon Technical Report (3.32 MB)
Kappes, J H, 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 (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. Int.~J.~Comp.~VisionPDF icon Technical Report (5.12 MB)
Schnörr, (1992). Computation of Discontinuous Optical Flow by Domain Decomposition and Shape Optimization. IJCV. 8 153--165
Rathke, F and Schnörr, C (2015). A Computational Approach to Log-Concave Density Estimation. An. St. Univ. Ovidius Constanta. 23 151-166PDF icon Technical Report (1.07 MB)
Rathke, F and Schnörr, C (2015). A Computational Approach to Log-Concave Density Estimation. An. St. Univ. Ovidius Constanta. 23 151-166
Lellmann, J and Schnörr, C (2011). Continuous Multiclass Labeling Approaches and Algorithms. CoRR. abs/1102.5448. http://arxiv.org/abs/1102.5448
Lellmann, J and Schnörr, C (2011). Continuous Multiclass Labeling Approaches and Algorithms. SIAM J.~Imag.~Sci. 4 1049-1096PDF icon Technical Report (4.31 MB)
Yuan, J, Schnörr, C and Steidl, G (2009). Convex Hodge Decomposition and Regularization of Image Flows. J.~Math.~Imag.~Vision. 33 169-177PDF icon Technical Report (1003.75 KB)
Swoboda, P and Schnörr, C (2013). Convex Variational Image Restoration with Histogram Priors. SIAM J.~Imag.~Sci. 6 1719-1735PDF icon Technical Report (553.54 KB)
Petra, S, Schnörr, C and Schröder, A (2013). Critical Parameter Values and Reconstruction Propertiesof Discrete Tomography: Application to Experimental FluidDynamics. Fundamenta Informaticae. 125 285--312PDF icon Technical Report (1.42 MB)
Schnörr, (1991). Determining Optical Flow for Irregular Domains by Minimizing Quadratic Functionals of a Certain Class. IJCV. 6 25--38
Cremers, D, Tischhäuser, F, Weickert, J and Schnörr, C (2002). Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford--Shah functional. Int.~J.~Computer Vision. 50 295--313
Lellmann, J, Lellmann, B, Widmann, F and Schnörr, C (2013). Discrete and Continuous Models for Partitioning Problems. Int.~J.~Comp.~Visionz. 104 241-269PDF icon Technical Report (4.74 MB)
Yuan, J, Schnörr, C and Mémin, E (2007). Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation. J.~Math.~Imag.~Vision. 28 67-80PDF icon Technical Report (752.44 KB)
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
Rohr, K and Schnörr, C (1993). An Efficient Approach to the Identification of Characteristic Intensity Variations. IVC. 11 273--277
Savchynskyy, B, Schmidt, S, Kappes, J H and Schnörr, C (2012). Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing. UAI. Proceedings. 746-755
Neumann, J, Schnörr, C and Steidl, G (2005). Efficient Wavelet Adaption for Hybrid Wavelet-Large Margin Classifiers. Pattern Recognition. 38 1815-1830
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--1314PDF icon Technical Report (439.9 KB)
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
Schnörr, (1993). On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow. PAMI. 15 1074--1079
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/10.1080/00207160.2011.634002PDF icon Technical Report (633.79 KB)
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/s10851-014-0546-8PDF icon Technical Report (1.97 MB)
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
Bruhn, A, Jakob, T, Fischer, M, Weickert, J, Brüning, U and Schnörr, C (2004). High performance cluster computing with 3-D nonlinear diffusion filters. Real-Time Imaging. 10 41--51
Gall, J, Potthoff, J, Schnörr, C, Rosenhahn, B and Seidel, H P (2007). Interacting and Annealing Particle Filters: Mathematics and a Recipe for Applications. J.~Math.~Imag.~Vision. 28 1--18PDF icon Technical Report (1.11 MB)
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
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
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
Bruhn, A, Weickert, J and Schnörr, C (2005). Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods. IJCV. 61 211-231
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. 87 291-308PDF icon Technical Report (1007.29 KB)
Breitenreicher, D and Schnörr, C (2011). Model-Based Multiple Rigid Object Detection and Registration in Unstructured Range Data. Int.~J.~Comp.~Vision. 92 32--52. http://www.springerlink.com/content/v266873267180602/PDF icon Technical Report (4.3 MB)

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