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Publications

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2000

Cremers, D, Schnörr, C, Weickert, J and Schellewald, C (2000). Diffusion Snakes Using Statistical Shape Knowledge. Proc. Algebraic Frames for the Perception-Action Cycle. Springer, Kiel. 1888 164–174

Cremers, D, Schnörr, C, Weickert, J and Schellewald, C (2000). Learning Translation Invariant Shape Knowledge for Steering Diffusion-Snakes. 3rd Workshop on Dynamic Perception. Akad. Verlagsges., Berlin, Germany. 9 117–122

2001

Keuchel, J, Schellewald, C, Cremers, D and Schnörr, C (2001). Convex Relaxations for Binary Image Partitioning and Perceptual Grouping. Mustererkennung 2001. Springer, Munich, Germany. 2191 353–360

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

Heiler, M, Cremers, D and Schnörr, C (2001). Efficient Feature Subset Selection For Support Vector Machines. Dept. Math. and Comp. Science, University of Mannheim, Germany

Cremers, D, Kohlberger, T and Schnörr, C (2001). Nonlinear Shape Statistics via Kernel Spaces. Mustererkennung 2001. Springer. 2191 269--276

Technical Report (324.55 KB)

Cremers, D, Kohlberger, T and Schnörr, C (2001). Nonlinear Shape Statistics via Kernel Spaces. Mustererkennung 2001. Springer, Munich, Germany. 2191 269–276

2002

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

Cremers, D and Schnörr, C (2002). Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 472–480

Cremers, D, Kohlberger, T and Schnörr, C (2002). Nonlinear Shape Statistics in Mumford-Shah Based Segmentation. Computer Vision -- ECCV 2002). Springer Verlag. 2351 93--108

Technical Report (636.58 KB)

Cremers, D, Kohlberger, T and Schnörr, C (2002). Nonlinear Shape Statistics in Mumford-Shah Based Segmentation. Computer Vision – ECCV 2002). Springer Verlag. 2351 93–108

Keuchel, J, Schnörr, C, Schellewald, C and Cremers, D (2002). Unsupervised Image Partitioning with Semidefinite Programming. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 141–149

2003

Keuchel, J, Schnörr, C, Schellewald, C and Cremers, D (2003). Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming. 25 1364–1379

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

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

Technical Report (1.67 MB)

Cremers, D and Schnörr, C (2003). Statistical Shape Knowledge in Variational Motion Segmentation. Image and Vision Comp. 21 77-86

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

Technical Report (451.82 KB)

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

2004

Cremers, D, Sochen, N and Schnörr, C (2004). Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. Computer Vision – ECCV 2004. Springer. 3024 74-86

2005

Bergtholdt, M, Cremers, D and Schnörr, C (2005). Variational Segmentation with Shape Priors. Handbook of Mathematical Models in Computer Vision. Springer. 147-160

2006

Cremers, D, Sochen, N and Schnörr, C (2006). Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. ijcv. 66 67-81

2009

Breitenreicher, D and Schnörr, C (2009). Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration Without Correspondence. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009). Springer. 5681 274-287. http://www.springerlink.com/content/1470n7577713069q/

Breitenreicher, D and Schnörr, C (2009). Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration Without Correspondence. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2009). Springer. 5681 274-287. http://www.springerlink.com/content/1470n7577713069q/

Technical Report (752.29 KB)

2011

Töppe, E, Oswald, M R, Cremers, D and Rother, C (2011). Image-based 3D modeling via cheeger sets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6492 LNCS 53–64

2012

Goldlücke, B, Strekalovskiy, E and Cremers, D (2012). The Natural Vectorial Total Variation which Arises from Geometric Measure Theory. SIAM Journal on Imaging Sciences. 5 537-563

Goldlücke, B, Strekalovskiy, E and Cremers, D (2012). The natural vectorial total variation which arises from geometric measure theory. SIAM Journal on Imaging Sciences

2013

Goldlücke, B, Strekalovskiy, E and Cremers, D (2013). Tight convex relaxations for vector-valued labeling. SIAM Journal on Imaging Sciences

2014

Goldlücke, B, Aubry, M, Kolev, K and Cremers, D (2014). A super-resolution framework for high-accuracy multiview reconstruction. Int. J. Comp. Vision. 106 172--191