Publications

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Journal Article
Schnörr, (2007). Signal and Image Approximation with Level-Set Constraints. Computing. 81 137-160PDF icon Technical Report (506.8 KB)
Cremers, D, Kohlberger, T and Schnörr, C (2003). Shape Statistics in Kernel Space for Variational Image Segmentation. Pattern Recognition. 36 1929--1943PDF icon Technical Report (1.67 MB)
Cremers, D, Kohlberger, T and Schnörr, C (2003). Shape Statistics in Kernel Space for Variational Image Segmentation. Pattern Recognition. 36 1929–1943
Breitenreicher, D and Schnörr, C (2010). Robust 3D object registration without explicit correspondence using geometric integration. Machine Vision and Applications. 21 601-611. http://www.springerlink.com/content/g20710062l014241/
Breitenreicher, D and Schnörr, C (2010). Robust 3D object registration without explicit correspondence using geometric integration. Machine Vision and Applications. 21 601-611. http://www.springerlink.com/content/g20710062l014241/PDF icon Technical Report (1.65 MB)
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. 18 781-794PDF icon Technical Report (4.07 MB)
Rathke, F, Schmidt, S and Schnörr, C (2014). Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization. Med. Image Anal. 18 781–794
Vlasenko, A and Schnörr, C (2010). Physically Consistent and Efficient Variational Denoising of Image Fluid Flow Estimates. IEEE Trans.~Image Proc. 19 586-595PDF icon Technical Report (2.65 MB)
Denitiu, A, Petra, S, Schnörr, C and Schnörr, C (2014). Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections. Fundamenta Informaticae. 135 73–102
Denitiu, A, Petra, S, Schnörr, C and Schnörr, C (2014). Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections. Fundamenta Informaticae. 135 73--102PDF icon Technical Report (2.24 MB)
Swoboda, P, Shekhovtsov, A, Kappes, J Hendrik, Schnörr, C and Savchynskyy, B (2016). Partial Optimality by Pruning for MAP-Inference with General Graphical Models. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE Computer Society. 38 1370–1382
Lellmann, J, Lenzen, F and Schnörr, C (2010). Optimality Bounds for Variational Relaxations of Optimal Partition Problems
Lellmann, J, Lenzen, F and Schnörr, C (2012). Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem. Journal of Mathematical Imaging and Vision. Springer. 47 239-257PDF icon Technical Report (616.16 KB)
Lellmann, J, Lenzen, F and Schnörr, C (2013). Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem. Journal of Mathematical Imaging and Vision. 47 (3) 239-257
Lellmann, J, Lenzen, F and Schnörr, C (2012). Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem. Journal of Mathematical Imaging and Vision. Springer. 47 239-257
Ruhnau, P and Schnörr, C (2007). Optical Stokes Flow Estimation: An Imaging-Based Control Approach. Exp.~in Fluids. 42 61--78PDF icon Technical Report (1.54 MB)
Zisler, M, Kappes, J H, Schnörr, C, Petra, S and Schnörr, C (2016). Non-Binary Discrete Tomography by Continuous Non-Convex Optimization. IEEE Comp. Imaging. 2 335-347
Cremers, D, Sochen, N and Schnörr, C (2006). Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. ijcv. 66 67-81
Bruhn, A, Weickert, J, Kohlberger, T and Schnörr, C (2006). A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods. Int.~J.~Computer Vision. 70 257-277PDF icon Technical Report (447.65 KB)
Bruhn, A, Weickert, J, Kohlberger, T and Schnörr, C (2006). A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods. Int. J. Computer Vision. 70 257-277
Kappes, J Hendrik, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2016). Multicuts and Perturb & MAP for Probabilistic Graph Clustering. Journal of Mathematical Imaging and Vision. 56 221–237. http://arxiv.org/abs/1601.02088
Schmitzer, B and Schnörr, C (2013). Modelling convex shape priors and matching based on the Gromov-Wasserstein distance. Journal of Mathematical Imaging and Vision. 46 143-159
Schmitzer, B and Schnörr, C (2013). Modelling convex shape priors and matching based on the Gromov-Wasserstein distance. Journal of Mathematical Imaging and Vision. 46 143-159PDF icon Technical Report (957.78 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/
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)
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)
Bruhn, A, Weickert, J and Schnörr, C (2005). Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods. 61 211-231
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 1–18
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)
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
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)
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)
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)
Savchynskyy, B, Schmidt, S, Kappes, J H and Schnörr, C (2012). Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing. UAI. Proceedings. 746-755
Rohr, K and Schnörr, C (1993). An Efficient Approach to the Identification of Characteristic Intensity Variations. 11 273–277

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