Publications

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Author Title [ Type(Desc)] Year
Journal Article
Hosni, A, Rhemann, C, Bleyer, M, Rother, C and Gelautz, M (2013). Fast cost-volume filtering for visual correspondence and beyond. IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 504–511
Storath, M and Weinmann, A (2018). Fast median filtering for phase or orientation data. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40 639–652PDF icon Technical Report (7.32 MB)
Rathke, F and Schnörr, C (2018). Fast Multivariate Log-Concave Density Estimation. preprint: ArXiv. https://arxiv.org/pdf/1805.07272.pdfPDF icon Technical Report (3.54 MB)
Rathke, F and Schnörr, C (2019). Fast Multivariate Log-Concave Density Estimation. Comp. Statistics & Data Analysis. 140 41-58
Rathke, F and Schnörr, C (2019). Fast Multivariate Log-Concave Density Estimation. Comp. Statistics & Data Analysis. 140 41–58
Rathke, F and Schnörr, C (2018). Fast Multivariate Log-Concave Density Estimation. preprint: arXiv. https://arxiv.org/pdf/1805.07272.pdf
Weickert, J, Heers, J, Schnörr, C, Zuiderveld, K –J, Scherzer, O and Stiehl, H –S (2001). Fast parallel algorithms for a broad class of nonlinear variational diffusion approaches. Real–Time Imaging. 7 31–45
Fortun, D, Storath, M, Rickert, D, Weinmann, A and Unser, M (2018). Fast Piecewise-Affine Motion Estimation Without Segmentation. IEEE Transactions on Image Processing. 27 5612 - 5624
Storath, M, Rickert, D, Unser, M and Weinmann, A (2017). Fast segmentation from blurred data in 3D fluorescence microscopy. IEEE Transactions on Image Processing. 26
Hamprecht, F A, Achleitner, U, Krismer, A C, Lindner, K H, Wenzel, V, Strohmenger, H - U, Thiel, W and van Gunsteren, W F (2001). Fibrillation power: An alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular fibrillation. Resuscitation. 50 287-296
Krall, K Ellen and Jähne, B (2013). First air-sea gas exchange laboratory study at hurricane wind speeds. Ocean Sci. Discuss. 10 1971--1996. www.ocean-sci-discuss.net/10/1971/2013/
Krall, K Ellen and Jähne, B (2014). First laboratory study of air-sea gas exchange at hurricane wind speeds. Ocean Sci. 10 257--265
Thieke, C, Nix, O, Koehn, A, Floca, R, van Straaten, D, Hahn, H, Strauss, L G, Siems, U, Graf, M, Pruem, H, Klein, J, Laue, H and Kaster, F O (2009). A framework and multi-application prototype for integrated radiological diagnostics and radiation therapy. Strahlentherapie und Onkologie. 185 81
Börner, K, Hermle, J, Sommer, C, Brown, N P, Knapp, B, Glass, B, Torralba, G, Reymann, J, Beil, N, Beneke, J, Pepperkok, R, Schneider, R and Ludwig, T (2010). From experimental setup to bioinformatics: An RNAi screening platform to identify host factors involved in HIV-1 replication. Biotechnology Journal. 5 39-49PDF icon Technical Report (556.09 KB)
Schnörr, (1993). On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow. pami. 15 1074–1079
Jähne, B, Brocke, M, Eisele, H, Hader, S, Hamprecht, F A, Happold, W, Raisch, F and Restle, J (2002). Für Anspruchsvolle - Multidimensionale Bildverarbeitung in der Produktion. Qualität und Zuverlässigkeit. 47 1154-1159
Lempitsky, V, Rother, C, Roth, S and Blake, A (2010). Fusion moves for markov random field optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32 1392–1405
Lempitsky, V, Rother, C, Roth, S and Blake, A (2010). Fusion moves for markov random field optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32 1392–1405
Blake, A, Criminisi, A, Cross, G, Kolmogorov, V and Rother, C (2007). Fusion of stereo, colour and contrast. Springer Tracts in Advanced Robotics. 28. www.research.microsoft.com/vision/cambridge
Röder, J, Tolosana-Delgado, R and Hamprecht, F A (2011). Gaussian process classification: singly versus doubly stochastic models, and new computational schemes. Stochastic Environmental Research & Risk Assessment. 25 (7) 865-879PDF icon Technical Report (672.68 KB)
Nicola, A, Petra, S, Popa, C and Schnörr, C (2011). A general extending and constraining procedure for linear iterative methods. Int. J. Comp. Math. http://dx.doi.org/10.1080/00207160.2011.634002
Nicola, A, Petra, S, Popa, C and Schnörr, C (2011). A general extending and constraining procedure for linear iterative methods. Int.~J.~Comp.~Math. http://dx.doi.org/10.1080/00207160.2011.634002PDF icon Technical Report (633.79 KB)
Schmähling, J and Hamprecht, F A (2007). Generalizing the Abbott-Firestone curve by two new surface descriptors. Wear. 262 1360-1371PDF icon Technical Report (877.34 KB)
Hamprecht, F A, Scott, W R P and van Gunsteren, W F (1997). Generation of pseudo-native protein structures for threading. Proteins. 28 522-529
Rubio, J C, Eigenstetter, A and Ommer, B (2015). Generative Regularization with Latent Topics for Discriminative Object Recognition. Pattern Recognition. Elsevier. 48 3871--3880PDF icon Technical Report (5.49 MB)
Aström, F and Schnörr, C (2017). A Geometric Approach for Color Image Regularization. Comp. Vision Image Understanding. 165 43–59. https://doi.org/10.1016/j.cviu.2017.10.013
Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2020). Geometric Numerical Integration of the Assignment Flow. Inverse Problems. 36 034004 (33pp)
Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2019). Geometric Numerical Integration of the Assignment Flow. Inverse Problems. https://doi.org/10.1088/1361-6420/ab2772
Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2018). Geometric Numerical Integration of the Assignment Flow. preprint: arXiv. https://arxiv.org/abs/1810.06970
Savchynskyy, B and Schmidt, S (2012). Getting Feasible Variable Estimates From Infeasible Ones: MRF Local Polytope Study. arXiv:1210.4081
Woodford, O J (2009). A Global Perspective on MAP Inference for Low-Level Vision Supplementary material to ICCV submission \# 1536. Optimization
Wanner, S, Straehle, C N and Goldlücke, B (2013). Globally Consistent Multi-Label Assignment on the Ray Space of 4D Light Fields. CVPR 2013. Proceedings. 1011-1018
Schmitzer, B and Schnörr, C (2015). Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes. J. Math. Imag. Vision. 52 436–458. http://link.springer.com/article/10.1007/s10851-014-0546-8
Schmitzer, B and Schnörr, C (2015). Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes. J.~Math.~Imag.~Vision. 52 436--458. http://link.springer.com/article/10.1007/s10851-014-0546-8PDF icon Technical Report (1.97 MB)
Kostrykin, L, Schnörr, C and Rohr, K (2019). Globally Optimal Segmentation of Cell Nuclei in Fluoroscence Microscopy Images using Shape and Intensity Information. Medical Image Analysis. https://doi.org/10.1016/j.media.2019.101536

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