Publications

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Karim, R, Bergtholdt, M, Kappes, J H and Schnörr, C (2007). Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification. Pattern Recognition -- 29th DAGM Symposium. Springer. 4713 395-404PDF icon Technical Report (491.56 KB)
Karim, R, Bergtholdt, M, Kappes, J H and Schnörr, C (2007). Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification. Pattern Recognition – 29th DAGM Symposium. Springer. 4713 395-404
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)
Abu Alhaija, H, Sellent, A, Kondermann, D and Rother, C (2015). Graphflow—6D large displacement scene flow via graph matching. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9358 285–296
Haja, A (2008). Graph-based Spatial Motion Tracking using Affine-covariant Regions. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8943
Vicente, S, Kolmogorov, V and Rother, C (2008). Graph cut based image segmentation with connectivity priors. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Beier, T (2014). Graph Based Image Analysis. University of Heidelberg
Zisler, M, Savarino, F, Petra, S and Schnörr, C (2017). Gradient Flows on a Riemannian Submanifold for Discrete Tomography. Proc. GCPR
Rother, C, Kolmogorov, V and Blake, A (2004). "GrabCut" - Interactive foreground extraction using iterated graph cuts. ACM Transactions on Graphics. 23 309–314
Wenig, M (2001). GOME-Spurenstoffauswertung und Bildverarbeitung. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Leue, C, Wenig, M, Jähne, B and Platt, U (1998). GOME mißt atmosphärische Stickoxide. Globale Biomassenverbrennung und Industrieemissionen. Physik in unserer Zeit. 29 179
Heers, J, Schnörr, C and Stiehl, H S (2001). Globally–Convergent Iterative Numerical Schemes for Non–Linear Variational Image Smoothing and Segmentation on a Multi–Processor Machine. IEEE Trans. Image Proc. 10 852–864
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
Schmitzer, B and Schnörr, C (2014). Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein ModesPDF icon Technical Report (2.9 MB)
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)
Schmitzer, B and Schnörr, C (2014). Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes
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
Kappes, J H, Speth, M, Andres, B, Reinelt, G and Schnörr, C (2011). Globally Optimal Image Partitioning by Multicuts. EMMCVPR. SpringerPDF icon Technical Report (7.47 MB)
Kappes, J Hendrik, Speth, M, Andres, B, Reinelt, G and Schnörr, C (2011). Globally Optimal Image Partitioning by Multicuts. EMMCVPR. Springer
Kappes, J H, Speth, M, Andres, B, Reinelt, G and Schnörr, C (2011). Globally Optimal Image Partitioning by Multicuts. EMMCVPR. Springer. 31-44PDF icon Technical Report (7.3 MB)
Andres, B, Kröger, T, Briggmann, K L, Denk, W, Norogod, N, Knott, G W, Köthe, U and Hamprecht, F A (2012). Globally Optimal Closed-Surface Segmentation for Connectomics. ECCV 2012. Proceedings, Part 3. 778-791PDF icon Technical Report (2.72 MB)
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
Wanner, S, Straehle, C N and Goldlücke, B (2013). Globally consistent multi-label assignment on the ray space of 4D light fields. IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Wanner, S and Goldlücke, B (2012). Globally Consistent Depth Labeling of 4D Lightfields. IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Wanner, S and Goldlücke, B (2012). Globally Consistent Depth Labeling of 4D Light Fields. CVPR. Proceedings. 41-48
Schnörr, C, Stiehl, H - S and Grigat, R - R (1996). On Globally Asymptotically Stable Continuous-Time CNNs for Adaptive Smoothing of Multidimensional Signals. Proc. 4th IEEE Int. Workshop on Cellular Neural Networks and their Applications. Seville, Spain
He, K, Rhemann, C, Rother, C, Tang, X and Sun, J (2011). A global sampling method for alpha matting. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2049–2056
Woodford, O J (2009). A Global Perspective on MAP Inference for Low-Level Vision Supplementary material to ICCV submission \# 1536. Optimization
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)
Savchynskyy, B, Kappes, J H, Swoboda, P and Schnörr, C (2013). Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation. NIPS. Proceedings. 1950-1958
Savchynskyy, B, Kappes, J Hendrik, Swoboda, P and Schnörr, C (2013). Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation. NIPS
Michel, F, Kirillov, A, Brachmann, E, Krull, A, Gumhold, S, Savchynskyy, B and Rother, C (2017). Global hypothesis generation for 6D object pose estimation. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua 115–124. http://arxiv.org/abs/1612.02287
Dierig, T (2002). Gewinnung von Tiefenkarten aus Fokusserien. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/2461
Savchynskyy, B and Schmidt, S (2013). Getting Feasible Variable Estimates From Infeasible Ones: MRF Local Polytope Study. Workshop on Inference for Probabilistic Graphical Models at ICCV. Proceedings
Savchynskyy, B and Schmidt, S (2012). Getting Feasible Variable Estimates From Infeasible Ones: MRF Local Polytope Study. arXiv:1210.4081

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