Christoph Schnörr
Christoph Schnörr
Professor of Mathematics and Computer Science, Heidelberg University
Verified email at
Cited by
Cited by
Lucas/Kanade meets Horn/Schunck: Combining local and global optic flow methods
A Bruhn, J Weickert, C Schnörr
International journal of computer vision 61, 211-231, 2005
Diffusion snakes: Introducing statistical shape knowledge into the Mumford-Shah functional
D Cremers, F Tischhäuser, J Weickert, C Schnörr
International journal of computer vision 50, 295-313, 2002
A theoretical framework for convex regularizers in PDE-based computation of image motion
J Weickert, C Schnörr
International Journal of Computer Vision 45, 245-264, 2001
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems
J Kappes, B Andres, FA Hamprecht, C Schnörr, S Nowozin, D Batra, ...
International Journal of Computer Vision 115 (2), 155-184, 2015
Variational optic flow computation with a spatio-temporal smoothness constraint
J Weickert, C Schnörr
Journal of mathematical imaging and vision 14, 245-255, 2001
Shape statistics in kernel space for variational image segmentation
D Cremers, T Kohlberger, C Schnörr
Pattern Recognition 36 (9), 1929-1943, 2003
Combined SVM-based feature selection and classification
J Neumann, C Schnörr, G Steidl
Machine learning 61, 129-150, 2005
Variational fluid flow measurements from image sequences: synopsis and perspectives
D Heitz, E Mémin, C Schnörr
Experiments in fluids 48, 369-393, 2010
Variational optical flow computation in real time
A Bruhn, J Weickert, C Feddern, T Kohlberger, C Schnorr
IEEE Transactions on Image Processing 14 (5), 608-615, 2005
Nonlinear shape statistics in mumford—shah based segmentation
D Cremers, T Kohlberger, C Schnörr
Computer Vision—ECCV 2002: 7th European Conference on Computer Vision …, 2002
A multigrid platform for real-time motion computation with discontinuity-preserving variational methods
A Bruhn, J Weickert, T Kohlberger, C Schnörr
International Journal of Computer Vision 70, 257-277, 2006
Variational optical flow estimation for particle image velocimetry
P Ruhnau, T Kohlberger, C Schnörr, H Nobach
Experiments in Fluids 38, 21-32, 2005
Towards recognition-based variational segmentation using shape priors and dynamic labeling
D Cremers, N Sochen, C Schnörr
Scale Space Methods in Computer Vision: 4th International Conference, Scale …, 2003
Probabilistic subgraph matching based on convex relaxation
C Schellewald, C Schnörr
International Workshop on Energy Minimization Methods in Computer Vision and …, 2005
Spine detection and labeling using a parts-based graphical model
S Schmidt, J Kappes, M Bergtholdt, V Pekar, S Dries, D Bystrov, ...
Information Processing in Medical Imaging: 20th International Conference …, 2007
A bayesian framework for multi-cue 3d object tracking
J Giebel, DM Gavrila, C Schnörr
Computer Vision-ECCV 2004: 8th European Conference on Computer Vision …, 2004
Convex multi-class image labeling by simplex-constrained total variation
J Lellmann, J Kappes, J Yuan, F Becker, C Schnörr
Scale Space and Variational Methods in Computer Vision: Second International …, 2009
A study of parts-based object class detection using complete graphs
M Bergtholdt, J Kappes, S Schmidt, C Schnörr
International journal of computer vision 87, 93-117, 2010
Pedestrian detection and tracking using a mixture of view-based shape–texture models
S Munder, C Schnorr, DM Gavrila
IEEE Transactions on intelligent transportation systems 9 (2), 333-343, 2008
Spectral clustering of linear subspaces for motion segmentation
F Lauer, C Schnörr
2009 IEEE 12th International Conference on Computer Vision, 678-685, 2009
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