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

C

J. Yuan, Steidl, G., and Schnörr, C., “Convex Hodge Decomposition of Image Flows”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 416--425.

Technical Report (290.72 KB)

J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., Schnörr, C., Mórken, K., and Lysaker, M., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.

J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, IWR, University of Heidelberg, 2008.

Technical Report (2.6 MB)

J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.

Technical Report (1.75 MB)

J. Lellmann, Becker, F., and Schnörr, C., “Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers”, in Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan, 2009, pp. 646-653.

J. Lellmann, Becker, F., and Schnörr, C., “Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers”, in IEEE International Conference on Computer Vision (ICCV), 2009, p. 646 -- 653.

Technical Report (930.18 KB)

F. Silvestri, Reinelt, G., and Schnörr, C., “A Convex Relaxation Approach to the Affine Subspace Clustering Problem”, in Proc.~GCPR, 2015.

Technical Report (878.63 KB)

P. Swoboda and Schnörr, C., “Convex Variational Image Restoration with Histogram Priors”, SIAM J.~Imag.~Sci., vol. 6, pp. 1719-1735, 2013.

Technical Report (553.54 KB)

S. Petra, Schnörr, C., and Schröder, A., “Critical Parameter Values and Reconstruction Propertiesof Discrete Tomography: Application to Experimental FluidDynamics”, Fundamenta Informaticae, vol. 125, p. 285--312, 2013.

Technical Report (1.42 MB)

D

F. Becker and Schnörr, C., “Decomposition of Quadratric Variational Problems”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 325--334.

F. Becker and Schnörr, C., “Decomposition of Quadratric Variational Problems”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 325--334.

Technical Report (1.29 MB)

A. Bruhn, Jakob, T., Fischer, M., Kohlberger, T., Weickert, J., Brüning, U., and Schnörr, C., “Designing 3–D Nonlinear Diffusion Filters for High Performance Cluster Computing”, in Pattern Recognition, Proc. 24th DAGM Symposium, Zürich, Switzerland, 2002, vol. 2449, pp. 290–297.

P. Fornland and Schnörr, C., “Determining the Dominant Plane from Uncalibrated Stereo Vision by a Robust and Convergent Iterative Approach without Correspondence”, in Proc. Int. Conf. Comp. Vision and Patt. Recog. (CVPR'97), San Juan, Puerto Rico, 1997.

D. Cremers, Tischhäuser, F., Weickert, J., and Schnörr, C., “Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford–Shah functional”, Int. J. Computer Vision, vol. 50, pp. 295–313, 2002.

D. Cremers, Schnörr, C., Weickert, J., and Schellewald, C., “Diffusion Snakes Using Statistical Shape Knowledge”, in Proc. Algebraic Frames for the Perception-Action Cycle, Kiel, 2000, vol. 1888, pp. 164–174.

D. Cremers, Schnörr, C., and Weickert, J., “Diffusion–Snakes: Combining Statistical Shape Knowledge and Image Information in a Variational Framework”, in IEEE First Workshop on Variational and Level Set Methods in Computer Vision, Vancouver, Canada, 2001, pp. 237–244.

A. Bruhn, Weickert, J., Kohlberger, T., and Schnörr, C., “Discontinuity-Preserving Computation of Variational Optic Flow in Real-Time”, in Scale-Space 2005, 2005, vol. 3459, pp. 279–290.

J. Lellmann, Lellmann, B., Widmann, F., and Schnörr, C., “Discrete and Continuous Models for Partitioning Problems”, Int.~J.~Comp.~Visionz, vol. 104, pp. 241-269, 2013.

Technical Report (4.74 MB)

J. Yuan, Schnörr, C., and Mémin, E., “Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation”, J.~Math.~Imag.~Vision, vol. 28, pp. 67-80, 2007.

Technical Report (752.44 KB)

M. Zisler, Petra, S., Schnörr, C., and Schnörr, C., “Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints”, in Proc. GCPR, 2016.

A. Stahl, Ruhnau, P., and Schnörr, C., “A Distributed Parameter Approach to Dynamic Image Motion”, in ECCV 2006, International Workshop on The Representation and Use of Prior Knowledge in Vision, 2006.

Technical Report (1.24 MB)

E

K. Rohr and Schnörr, C., “An Efficient Approach to the Identification of Characteristic Intensity Variations”, vol. 11, pp. 273–277, 1993.

B. Savchynskyy, Schmidt, S., Kappes, J. H., and Schnörr, C., “Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing”, in UAI 2012, 2012.

Technical Report (529 KB)

B. Savchynskyy, Schmidt, S., Kappes, J. H., and Schnörr, C., “Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing”, UAI. Proceedings, pp. 746-755, 2012.

B. Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., “An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM”, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010, pp. 353-362.

B. Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., “An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM”, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010.

Technical Report (218.43 KB)

A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography”, in Discrete Geometry for Computer Imagery (DGCI) 2014, 2014, pp. 262–274.

A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography”, in Discrete Geometry for Computer Imagery (DGCI) 2014, 2014, p. 262--274.

Technical Report (894.83 KB)

A. Neufeld, Berger, J., Becker, F., Lenzen, F., and Schnörr, C., “Estimating Vehicle Ego-Motion and Piecewise Planar Scene Structure from Optical Flow in a Continuous Framework”, in 37th German Conference on Pattern Recognition, 2015.

C. Schellewald, Roth, S., and Schnörr, C., “Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views”, Image Vision Comp., vol. 25, p. 1301--1314, 2007.

Technical Report (439.9 KB)

S. Schmidt, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization”, in EMMCVPR 2011, 2011, vol. 6819, pp. 89-103.

S. Schmidt, Savchynskyy, B., Kappes, J. Hendrik, and Schnörr, C., “Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization”, in EMMCVPR, 2011, vol. 6819, pp. 89-103.

S. Schmidt, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization”, in EMMCVPR, 2011, vol. 6819, pp. 89-103.

Technical Report (684.13 KB)

S. Petra, Popa, C., and Schnörr, C., “Extended and Constrained Cimmino-type Algorithms with Applications in Tomographic Image Reconstruction”, IWR, University of Heidelberg, 2008.

S. Petra, Popa, C., and Schnörr, C., “Extended and Constrained Cimmino-type Algorithms with Applications in Tomographic Image Reconstruction”, IWR, University of Heidelberg, 2008.

Technical Report (2.13 MB)

Pages