Publications

Search

Show only items where

Author

Type

Term

Year

Keyword

Export 223 results:

Filters: Author is Christoph Schnörr [Clear All Filters]

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

S

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)

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.

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.

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.

T

J. H. Kappes, Petra, S., Schnörr, C., and Zisler, M., “TomoGC: Binary Tomography by Constrained Graph Cuts”, in Proc.~GCPR, 2015.

Technical Report (2.46 MB)

S. Petra and Schnörr, C., “TomoPIV meets Compressed Sensing”, IWR, University of Heidelberg, 2009.

Technical Report (646.75 KB)

S. Petra and Schnörr, C., “TomoPIV meets Compressed Sensing”, Pure Math.~Appl., vol. 20, p. 49 -- 76, 2009.

Technical Report (409.1 KB)

J. Yuan, Schnörr, C., and Steidl, G., “Total-Variation Based Piecewise Affine Regularization”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 552-564.

Technical Report (478.04 KB)

J. Yuan, Schnörr, C., and Steidl, G., “Total-Variation Based Piecewise Affine Regularization”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 552-564.

J. H. Kappes, Speth, M., Reinelt, G., and Schnörr, C., “Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization”, in CVPR, 2013.

Technical Report (623.84 KB)

J. H. Kappes, Speth, M., Reinelt, G., and Schnörr, C., “Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization”, in CVPR, 2013.

D. Cremers, Sochen, N., and Schnörr, C., “Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling”, in Scale Space Methods in Computer Vision, 2003, vol. 2695, p. 388--400.

Technical Report (451.82 KB)

D. Cremers, Sochen, N., and Schnörr, C., “Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling”, in Scale Space Methods in Computer Vision, 2003, vol. 2695, pp. 388–400.

V

F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., “Variational Adaptive Correlation Method for Flow Estimation”, IEEE Transactions on Image Processing, vol. 21, 6, pp. 3053 - 3065, 2011.

F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., “Variational Adaptive Correlation Method for Flow Estimation”, IEEE Transactions on Image Processing, vol. 21, p. 3053 -- 3065, 2012.

Technical Report (18.81 MB)

F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., “Variational Adaptive Correlation Method for Flow Estimation”, IEEE Transactions on Image Processing, vol. 21, pp. 3053 – 3065, 2012.

F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry"”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, pp. 335-344.

F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 335--344.

Technical Report (1.82 MB)

F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry”, in Pattern Recognition – 30th DAGM Symposium, 2008, vol. 5096, pp. 335–344.

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

Technical Report (3.39 MB)

F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “Variational Correlation Approach to Flow Measurement with Window Adaption”, in 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2008, p. 1.1.8.

F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “Variational Correlation Approach to Flow Measurement with Window Adaption”, in 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2008, p. 1.1.3.

Technical Report (3.37 MB)

F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “Variational Correlation Approach to Flow Measurement with Window Adaption”, in 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2008, p. 1.1.3.

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

Technical Report (842.06 KB)

D. Heitz, Mémin, E., and Schnörr, C., “Variational fluid flow measurements from image sequences: synopsis and perspectives”, Exp.~Fluids, vol. 48, pp. 369-393, 2010.

Technical Report (1.91 MB)

F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “Variational Image Denoising with Adaptive Constraint Sets”, in Proceedings of the 3nd International Conference on Scale Space and Variational Methods in Computer Vision 2011, in press, 2011, vol. 6667, pp. 206-217.

F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “Variational Image Denoising with Adaptive Constraint Sets”, in LNCS, 2012, pp. 206-217.

Technical Report (649.03 KB)

F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “Variational Image Denoising with Adaptive Constraint Sets”, in Proceedings of the 3rd International Conference on Scale Space and Variational Methods in Computer Vision 2011, 2012, pp. 206-217.

P. Swoboda and Schnörr, C., “Variational Image Segmentation and Cosegmentation with the Wasserstein Distance”, in Energy Minimization Methods in Computer Vision and Pattern Recognition, 2013, vol. 8081, p. 321--334.

Technical Report (8.06 MB)

P. Swoboda and Schnörr, C., “Variational Image Segmentation and Cosegmentation with the Wasserstein Distance”, in Energy Minimization Methods in Computer Vision and Pattern Recognition, 2013, vol. 8081, pp. 321–334.

Pages