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Filters: Author is Christoph Schnörr and First Letter Of Title is S [Clear All Filters]

Conference Paper

J. Berger, Neufeld, A., Becker, F., Lenzen, F., and Schnörr, C., “Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations”, in Scale Space and Variational Methods in Computer Vision (SSVM 2015), 2015.

Technical Report (364.01 KB)

B. Andres, Hamprecht, F. A., and Garbe, C. S., “Selection of Local Optical Flow Models by Means of Residual Analysis”, in Pattern Recognition, 2007, vol. 4713, pp. 72-81.

Technical Report (229.64 KB)

B. Andres, Garbe, C. S., Schnörr, C., and Jähne, B., “Selection of local optical flow models by means of residual analysis”, in Proceedings of the 29th DAGM Symposium on Pattern Recognition, 2007, p. 72--81.

L. Görlitz, Menze, B. H., Weber, M. - A., and Kelm, B. Michael, “Semi-Supervised Tumor Detection in MRSI With Discriminative Random Fields”, in Pattern Recognition, 2007, vol. 4713, pp. 224-233.

Technical Report (872.46 KB)

S. Petra, Schröder, A., Wieneke, B., and Schnörr, C., “On Sparsity Maximization in Tomographic Particle Image Reconstruction”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 294--303.

Technical Report (1014.71 KB)

F. Lauer and Schnörr, C., “Spectral Clustering of Linear Subspaces for Motion Segmentation”, in Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan, in press, 2009, pp. 678-685.

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

Technical Report (1.12 MB)

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

Technical Report (1.46 MB)

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

Technical Report (408.99 KB)

J. Yuan, Schnörr, C., Steidl, G., and Becker, F., “A Study of Non-Smooth Convex Flow Decomposition”, in Proc. Variational, Geometric and Level Set Methods in Computer Vision, 2005, vol. 3752, pp. 1–12.

In Collection

M. Bergtholdt and Schnörr, C., “Shape Priors and Online Appearance Learning for Variational Segmentation and Object Recognition in Static Scenes”, Pattern Recognition, Proc. 27th DAGM Symposium, vol. 3663. Springer, pp. 342–350, 2005.

Journal Article

D. Cremers, Kohlberger, T., and Schnörr, C., “Shape Statistics in Kernel Space for Variational Image Segmentation”, Pattern Recognition, vol. 36, p. 1929--1943, 2003.

Technical Report (1.67 MB)

D. Cremers, Kohlberger, T., and Schnörr, C., “Shape Statistics in Kernel Space for Variational Image Segmentation”, Pattern Recognition, vol. 36, pp. 1929–1943, 2003.

C. Schnörr, “Signal and Image Approximation with Level-Set Constraints”, Computing, vol. 81, pp. 137-160, 2007.

Technical Report (506.8 KB)

J. Yuan, Schnörr, C., and Steidl, G., “Simultaneous Optical Flow Estimation and Decomposition”, SIAM J.~Scientific Computing, vol. 29, pp. 2283-2304, 2007.

Technical Report (1.16 MB)

F. Lenzen, Lellmann, J., Becker, F., and Schnörr, C., “Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets”, SIAM J.~Imag.~Sci., vol. 7, p. 2139--2174, 2014.

Technical Report (802.13 KB)

F. Lenzen, Lellmann, J., Becker, F., and Schnörr, C., “Solving QVIs for Image Restoration with Adaptive Constraint Sets”, SIAM Journal on Imaging Sciences (SIIMS), in press, 2014.

D. Breitenreicher, Lellmann, J., and Schnörr, C., “Sparse Template-Based Variational Image Segmentation”, Advances in Adaptive Data Analysis, vol. 3, pp. 149-166, 2011.

Technical Report (866.28 KB)

D. Breitenreicher, Lellmann, J., and Schnörr, C., “Sparse Template-Based Variational Image Segmentation”, Advances in Adaptive Data Analysis, vol. 3, pp. 149-166, 2011.

D. Cremers and Schnörr, C., “Statistical Shape Knowledge in Variational Motion Segmentation”, Image and Vision Comp., vol. 21, pp. 77-86, 2003.

B. Savchynskyy, Kappes, J. H., Schmidt, S., and Schnörr, C., “A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling”, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), accepted as oral presentation, pp. 1817 - 1823, 2011.

M. Bergtholdt, Kappes, J. H., Schmidt, S., and Schnörr, C., “A Study of Parts-Based Object Class Detection Using Complete Graphs”, Int.~J.~Comp.~Vision, vol. 87, pp. 93-117, 2010.

Technical Report (2.18 MB)

M. Bergtholdt, Kappes, J. H., Schmidt, S., and Schnörr, C., “A Study of Parts-Based Object Class Detection Using Complete Graphs”, Int. J. Comp. Vision, vol. 87, pp. 93-117, 2010.