Publications

Export 1916 results:
Author Title [ Type(Desc)] Year
Journal Article
Didden, E - M, Thorarinsdottir, T L, Lenkoski, A and Schnörr, C (2015). Shape from Texture using Locally Scaled Point Processes. Image Anal. Stereol. 34 161-170
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--1943PDF icon Technical Report (1.67 MB)
Milbich, T, Roth, K, Brattoli, B and Ommer, B (2020). Sharing Matters for Generalization in Deep Metric Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). https://arxiv.org/abs/2004.05582
Schnörr, (2007). Signal and Image Approximation with Level-Set Constraints. Computing. 81 137-160
Schnörr, (2007). Signal and Image Approximation with Level-Set Constraints. Computing. 81 137-160PDF icon Technical Report (506.8 KB)
Hanselmann, M, Voss, B, Renard, B Y, Lindner, M, Köthe, U, Kirchner, M and Hamprecht, F A (2011). SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists. Bioinformatics. 27 (7) 987-993PDF icon Technical Report (2.2 MB)
Jähne, (1997). SIMD-Bildverarbeitungsalgorithmen mit dem Multimedia Extension-Instruktionssatz (MMX) von Intel. Automatisierungstechnik. 10 453--460
Köthe, U, Herrmannsdörfer, F, Kats, I and Hamprecht, F A (2014). SimpleSTORM: a fast, self-calibrating reconstruction algorithm for localization microscopy. Histochemistry and Cell Biology. 141 613-627PDF icon Technical Report (2.29 MB)
Yuan, J, Schnörr, C and Steidl, G (2007). Simultaneous Optical Flow Estimation and Decomposition. SIAM J.~Scientific Computing. 29 2283-2304PDF icon Technical Report (1.16 MB)
Yuan, J, Schnörr, C and Steidl, G (2007). Simultaneous Optical Flow Estimation and Decomposition. SIAM J. Scientific Computing. 29 2283-2304
Storath, M, Kiefer, L and Weinmann, A (2019). Smoothing for signals with discontinuities using higher order Mumford-Shah models. Numerische Mathematik. 143(2) 423-460PDF icon Technical Report (1.09 MB)
Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J. Imag. Sci. 7 2139–2174
Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets. SIAM J.~Imag.~Sci. 7 2139--2174PDF icon Technical Report (802.13 KB)
Lenzen, F, Lellmann, J, Becker, F and Schnörr, C (2014). Solving QVIs for Image Restoration with Adaptive Constraint Sets. SIAM Journal on Imaging Sciences (SIIMS), in press
Rother, C (2011). Sparse Higher Order Functions of Discrete Variables–-Representation and Optimization. research.microsoft.com. 45. http://research.microsoft.com/pubs/147370/RotherKohli-SparseHigherOrder.pdf
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166
Breitenreicher, D, Lellmann, J and Schnörr, C (2011). Sparse Template-Based Variational Image Segmentation. Advances in Adaptive Data Analysis. 3 149-166PDF icon Technical Report (866.28 KB)
Wagner, T, Leue, C, Wenig, M, Pfeilsticker, K and Platt, U (2001). Spatial and temporal distribution of enhanced boundary layer BrO concentrations measured by the GOME instrument aboard ERS-2. J. Geophys. Res. 106 24225--24235
Uttenweiler, D, Weber, C, Jähne, B, Fink, R H A and Schaar, H (2003). Spatiotemporal anisotropic diffusion filtering to improve signal-to-noise ratios and object restoration in fluorescence microscopic image sequences.. J Biomed Opt. Ruprecht-Karls-Universität Heidelberg, Institut für Physiologie und Pathophysiologie Medical Biophysics, Im Neuenheimer Feld 326, 69120 Heidelberg, Germany. dietmar.uttenweiler@urz.uni-heidelberg.de. 8 40--47. http://dx.doi.org/10.1117/1.1527627
Antic, B and Ommer, B (2015). Spatio-temporal Video Parsing for Abnormality Detection. arXiv. abs/1502.06235. http://arxiv.org/abs/1502.06235PDF icon Technical Report (4.61 MB)
Rahaman, N, Arpit, D, Baratin, A, Draxler, F, Lin, M, Hamprecht, F A, Bengio, Y and Courville, A (2018). On the spectral bias of deep neural networks. arXiv preprint arXiv:1806.08734
Jäger, M, Humbert, S and Hamprecht, F A (2008). Sputter Tracking for the Automatic Monitoring of Industrial Laser Welding Processes. IEEE Transactions on Industrial Electronics. 55 2177-2184PDF icon Technical Report (1.83 MB)
Cremers, D and Schnörr, C (2003). Statistical Shape Knowledge in Variational Motion Segmentation. Image and Vision Comp. 21 77-86
Hamprecht, F A, Peter, C, Daura, X, Thiel, W and van Gunsteren, W F (2001). A strategy for analysis of (molecular) equilibrium simulations: configuration space density estimation, clustering and visualization. Journal of Chemical Physics. 114 2079-2089
Rathke, F, Hansen, K, Brefeld, U and Müller, K - R (2010). StructRank: A new approach for ligand-based virtual screening. J. Chem. Inf. Model. 51 83–92
Schurr, U, Schuberth, B, Aloni, R, Pradel, K S, Schmund, D, Jähne, B and Ullrich, C I (1996). Structural and functional evidence for xylem-mediated water transport and high tranpiration in Agrobacterium tumefaciens-induced tumors of Ricinus communis. Botanica Acta. 109 405--412
Lou, X and Hamprecht, F A (2012). Structured Learning from Partial Annotations. ICML 2012. Proceedings. http://icml.cc/discuss/2012/753.htmlPDF icon Technical Report (843.45 KB)
Schnörr, (1998). A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction. J. of Math. Imag. and Vision. 8 271–292
Savchynskyy, B, Kappes, J H, Schmidt, S and Schnörr, C (2011). 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. 1817 - 1823
Bergtholdt, M, Kappes, J H, Schmidt, S and Schnörr, C (2010). A Study of Parts-Based Object Class Detection Using Complete Graphs. Int. J. Comp. Vision. 87 93-117. http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s11263-009-0209-1
Bergtholdt, M, Kappes, J H, Schmidt, S and Schnörr, C (2010). A Study of Parts-Based Object Class Detection Using Complete Graphs. Int.~J.~Comp.~Vision. 87 93-117. http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s11263-009-0209-1PDF icon Technical Report (2.18 MB)
Zhang, X and Garbe, C S (2004). Studying dynamical processes of air-sea exchanges with air-water interface image techniques. Recent Research Developments in Fluid Dynamics. 5 57--87. www-pord.ucsd.edu/~xzhang/publication/fd1.pdf
Desana, M and Schnörr, C (2020). Sum-Product Graphical Models. Machine Learning. 109 135–173
Desana, M and Schnörr, C (2019). Sum-Product Graphical Models. Machine Learning. https://doi.org/10.1007/s10994-019-05813-2

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