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Schilling, H, Diebold, M, Gutsche, M and Jähne, B (2017). On the design of a fractal calibration pattern for improved camera calibration. tm - Technisches Messen. 84 440–451
Schiegg, M, Diego, F and Hamprecht, F A (2016). Learning Diverse Models: The Coulomb Structured Support Vector Machine. ECCV. Proceedings. Springer. LNCS 9907 585-599PDF icon Technical Report (2.54 MB)
Schiegg, M (2015). Multi-Target Tracking with Probabilistic Graphical Models. University of Heidelberg
Schiegg, M, Hanslovsky, P, Haubold, C, Köthe, U, Hufnagel, L and Hamprecht, F A (2015). Graphical Model for Joint Segmentation and Tracking of Multiple Dividing Cell. Bioinformatics. 31 948-956. http://bioinformatics.oxfordjournals.org/content/early/2014/11/17/bioinformatics.btu764.full.pdf?keytype=ref&ijkey=mTXWsiFrci7R8tcPDF icon Technical Report (534.29 KB)
Schiegg, M, Hanslovsky, P, Kausler, B X, Hufnagel, L and Hamprecht, F A (2013). Conservation Tracking. ICCV 2013. Proceedings. 2928--2935PDF icon Technical Report (5.22 MB)
Schiegg, M, Heuer, B, Haubold, C, Wolf, S, Köthe, U and Hamprecht, F A (2015). Proof-reading Guidance in Cell Tracking by Sampling from Tracking-by-assignment Models. ISBI. Proceedings. 394-398PDF icon Technical Report (648.55 KB)
Scheuermann, T, Pfundt, G, Eyerer, P and Jähne, B (1995). Oberflächenkonturvermessung mikroskopischer Objekte durch Projektion statistischer Rauschmuster. Proc. 17. DAGM-Symposium Mustererkennung, Bielefeld, 13.-15. September 1995. 319--326
Schelten, K, Nowozin, S, Jancsary, J, Rother, C and Roth, S (2015). Interleaved regression tree field cascades for blind image deconvolution. Proceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015. 494–501
Schellewald, C, Keuchel, J and Schnörr, C (2001). Image labeling and grouping by minimizing linear functionals over cones. Proc. Third Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'01). Springer, INRIA, Sophia Antipolis, France. 2134 267–282
Schellewald, C, Roth, S and Schnörr, C (2001). Evaluation of Convex Optimization Techniques for the Weighted Graph–Matching Problem in Computer Vision. Mustererkennung 2001. Springer, Munich, Germany. 2191 361–368
Schellewald, C, Roth, S and Schnörr, C (2007). Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views. Image Vision Comp. 25 1301–1314
Schellewald, C, Roth, S and Schnörr, C (2002). Performance Evaluation Of A Convex Relaxation Approach To The Quadratic Assignment Of Relational Object Views. Dept. Math. and Comp. Science, University of Mannheim, Germany
Schellewald, C, Roth, S and Schnörr, C (2001). Application Of Convex Optimization Techniques To The Relational Matching Of Object Views. Dept. Math. and Comp. Science, University of Mannheim, Germany
Schellewald, C and Schnörr, C (2005). Probabilistic Subgraph Matching Based on Convex Relaxation. Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 171-186
Schellewald, C and Schnörr, C (2003). Subgraph Matching with Semidefinite Programming. Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'03). Palermo, Italy
Schellewald, C, Roth, S and Schnörr, C (2007). Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views. Image Vision Comp. 25 1301--1314PDF icon Technical Report (439.9 KB)
Scheelen, C (2010). Automated Quality Control In The Life Sciences. University of Heidelberg
Schaum, M (1993). Subpixelgenaue Positionsbestimmungen In Digitalen Bildern. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Scharr, H (2000). Optimale Operatoren in der Digitalen Bildverarbeitung. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/962
Scharr, H (2000). Optimal Separable Interpolation Of Color Images With Bayer Array Format. DFG research unit Image Sequence Analysis to Investigate Dynamic Processes, Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany. http://www.ub.uni-heidelberg.de/archiv/12680/
Scharr, H (1996). Digitale Bildverarbeitung Und Papier Texturanalyse Mittels Pyramiden Und Grauwertstatistiken Am Beispiel Der Papierformation. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Scharr, H, Jähne, B, Böckle, S, Kazenwadel, J, Kunzelmann, T, Schulz, C and Krüger, N (2000). Flame front analysis in turbulent combustion. Mustererkennung 2000. Springer. 325--332
Scharr, H, Körkel, S and Jähne, B (1997). Numerische Isotropieoptimierung von FIR-Filtern mittels Querglättung. Proceedings of the 19th DAGM Symposium on Pattern Recognition, Braunschweig. 199--208
Scharr, H and Küsters, R (2002). A linear model for simultaneous estimation of 3D motion and depth. Proceedins of IEEE Workshop on Motion and Video Computing 2002, Orlando
Scharr, H and Weickert, J (2000). An anisotropic diffusion algorithm with optimized rotation invariance. Proceedings of the 22th DAGM Symposium on Pattern Recognition. 460--467
Schapowalow, A (2011). Implementierung Der "Focus-Sweep" Technik Mit Hilfe Von Scheimpflugoptik Und Tdi-Technik. University of Heidelberg
Schapowalow, A (2011). Implementierung Der Focus-Sweep Technik Mit Hilfe Von Scheimpflugoptik Und Tdi-Technik. Fakultät für Mathematik und Informatik, Ruprecht-Karls-Universität Heidelberg, Germany
Schaper, J (2011). Wave Height Estimation With Stereo Images Of The Reflective Stereo Slope Gauge (Rssg). Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Schäfer, H, Lenzen, F and Garbe, C S (2013). Depth and Intensity Based Edge Detection in Time-of-Flight Images. 3DV-Conference, 2013 International Conference on. 111-118PDF icon Technical Report (1.85 MB)
Schäfer, H, Lenzen, F and Garbe, C S (2013). Depth and Intensity Based Edge Detection in Time-of-Flight Images. 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2013 International Conference on. IEEE. 111-118
Schäfer, H, Lenzen, F, Meister, S and Garbe, C S (2012). Edge Detection in Time-of-Flight Images. submitted to ECCV, 2nd Workshop on Consumer Depth Cameras for Computer Vision
Schäfer, H, Lenzen, F and Garbe, C S (2014). Model based scattering correction in time-of-flight cameras. Optics Express. 22 29835-29846
Sayed, N, Brattoli, B and Ommer, B (2018). Cross and Learn: Cross-Modal Self-Supervision. German Conference on Pattern Recognition (GCPR) (Oral). Stuttgart, Germany. https://arxiv.org/abs/1811.03879v1PDF icon Article (891.47 KB)PDF icon Oral slides (9.17 MB)
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)PDF icon Technical Report (408.99 KB)
Savchynskyy, B, Kappes, J H, Swoboda, P and Schnörr, C (2013). Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation. NIPSPDF icon Technical Report (499.17 KB)

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