Publications

Export 1852 results:
Author Title [ Type(Desc)] Year
Journal Article
Zern, A, Zisler, M, Petra, S and Schnörr, C (2019). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. preprint: arXiv. https://arxiv.org/abs/1904.10863
Zern, A, Zisler, M, Petra, S and Schnörr, C (2020). Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment. Journal of Mathematical Imaging and Vision. https://doi.org/10.1007/s10851-019-00935-7
Milbich, T, Ghori, O and Ommer, B (2020). Unsupervised Representation Learning by Discovering Reliable Image Relations. Pattern Recognition. 102. http://arxiv.org/abs/1911.07808
Kohli, P, Nickisch, H, Rother, C and Rhemann, C (2012). User-centric learning and evaluation of interactive segmentation systems. International Journal of Computer Vision. 100 261–274
Kelm, B Michael, Kaster, F O, Henning, A, Weber, M - A, Bachert, P, Bösinger, P, Hamprecht, F A and Menze, B H (2011). Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images. NMR in Biomedicine. 25(1) 1-13PDF icon Technical Report (1.94 MB)
Becker, F, Wieneke, B, Petra, S, Schröder, A and Schnörr, C (2011). Variational Adaptive Correlation Method for Flow Estimation. IEEE Transactions on Image Processing. 21, 6 3053 - 3065
Becker, F, Wieneke, B, Petra, S, Schröder, A and Schnörr, C (2012). Variational Adaptive Correlation Method for Flow Estimation. IEEE Transactions on Image Processing. 21 3053 – 3065
Becker, F, Wieneke, B, Petra, S, Schröder, A and Schnörr, C (2012). Variational Adaptive Correlation Method for Flow Estimation. IEEE Transactions on Image Processing. 21 3053 -- 3065PDF icon Technical Report (18.81 MB)
Ruhnau, P, Gütter, C, Putze, T and Schnörr, C (2005). A variational approach for particle tracking velocimetry. Meas. Science and Techn. 16 1449-1458
Schnörr, C, Sprengel, R and Neumann, B (1996). A Variational Approach to the Design of Early Vision Algorithms. Computing Suppl. 11 149-165
Ruhnau, P, Stahl, A and Schnörr, C (2007). Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization. Measurement Science and Technology. 18 755-763PDF icon Technical Report (842.06 KB)
Ruhnau, P, Stahl, A and Schnörr, C (2007). Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization. Measurement Science and Technology. 18 755-763
Heitz, D, Mémin, E and Schnörr, C (2010). Variational fluid flow measurements from image sequences: synopsis and perspectives. Exp.~Fluids. 48 369-393PDF icon Technical Report (1.91 MB)
Heitz, D, Mémin, E and Schnörr, C (2010). Variational fluid flow measurements from image sequences: synopsis and perspectives. Exp. Fluids. 48 369-393
Wanner, S and Goldlücke, B (2014). Variational light field analysis for disparity estimation and super-resolution. IEEE Trans. Pattern Analysis Machine Intelligence. 36 606--619
Bruhn, A, Weickert, J, Feddern, C, Kohlberger, T and Schnörr, C (2005). Variational optic flow computation in real-time. IEEE Trans. Image Proc. 14 608–615
Weickert, J and Schnörr, C (2001). Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint. J. Math. Imaging and Vision. 14 245–255
Ruhnau, P, Kohlberger, T, Nobach, H and Schnörr, C (2005). Variational Optical Flow Estimation for Particle Image Velocimetry. Experiments in Fluids. 38 21--32PDF icon Technical Report (1.21 MB)
Ruhnau, P, Kohlberger, T, Nobach, H and Schnörr, C (2005). Variational Optical Flow Estimation for Particle Image Velocimetry. Experiments in Fluids. 38 21–32
Becker, F, Lenzen, F, Kappes, J H and Schnörr, C (2013). Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences. International Journal of Computer Vision. 105 (3) 269-297
Becker, F, Lenzen, F, Kappes, J H and Schnörr, C (2013). Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences. International Journal of Computer Vision. Springer US. 105 269–297. http://dx.doi.org/10.1007/s11263-013-0639-7
Becker, F, Lenzen, F, Kappes, J H and Schnörr, C (2013). Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences. International Journal of Computer Vision. Springer US. 105 269--297. http://dx.doi.org/10.1007/s11263-013-0639-7PDF icon Technical Report (15.4 MB)
Kleesiek, J, Petersen, J, Döring, M, Maier-Hein, K, Köthe, U, Wick, W, Hamprecht, F A, Bendszus, M and Biller, A (2016). Virtual Raters for Reproducible and Objective Assessments in Radiology. Nature Scientific Reports. 6PDF icon Technical Report (2.81 MB)
Gianniotis, N and Tiño, P (2009). Visualization of Structured Data via Generative Probabilistic Modeling. Pattern Recognition. Springer. 5400 118-137
Pfannmöller, M, Flügge, H, Benner, G, Wacker, I, Sommer, C, Hanselmann, M, Schmale, S, Schmidt, H, Hamprecht, F A, Rabe, T, Kowalsky, W and Schröder, R (2011). Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy. Nano Letters. 11 3099-3107
Hamprecht, F A and Jähne, B (2004). Vom Bild zur Information. Ruperto Carola -- Forschungsmagazin der Universität Heidelberg. 03.2004 9-12
Jäger, M, Knoll, C and Hamprecht, F A (2008). Weakly Supervised Learning of a Classifier for Unusual Event Detection. IEEE Transactions on Image Processing. 17 1700-1708PDF icon Technical Report (295.32 KB)
Jähne, B, Köhler, H - J, Rath, R and Wierzimok, D (1993). Wellenamplitudenmessungen mittels videometrischer Bildverarbeitung. Mitteilungsblatt der Bundesanstalt für Wasserbau. 70 27--62
Meister, S, Izadi, S, Kohli, P and M Hämmerle, M \ (2012). When can we use KinectFusion for ground truth acquisition?. Proc Workshop on \ldots. 3–8. http://meshlab.sourceforge.net/ http://www.msr-waypoint.net/en-us/um/people/pkohli/papers/mikhrk_iros_dataset_2012.pdf%5Cnpapers3://publication/uuid/2615CF9D-C632-4E39-B1C4-B32A4A5D339C
Márquez-Valle, P, Gil, D, Hernàndez-Sabaté, A and Kondermann, D (2013). When is a confidence measure good enough?. submitted to CVPR 2013
Renard, B Y, Kirchner, M, Monigatti, F, Ivanov, A R, Rappsilber, J, Winter, D, Steen, J A J, Hamprecht, F A and Steen, H (2009). When Less Can Yield More - Computational Preprocessing of MS/MS Spectra for Peptide Identification Preprocessing. Proteomics. 9 4978-4984PDF icon Technical Report (901.78 KB)
Jähne, (1999). When the invisible becomes visible. German research, Magazine of the German Research Foundation (DFG). 30--33
Horvát, E - A, Hanselmann, M, Hamprecht, F A and Zweig, K A (2012). You Are Who Knows You: Predicting Links Between Non-Members of Facebook. European Conference on Complex Systems. Proceedings. 3 309-315PDF icon Technical Report (1.92 MB)
Jähne, (2008). Zukunftsperspektiven der industriellen Bildverarbeitung - Was kann die akademische Forschung beitragen?. Optik & Photonik. 3 28-33
Masters Thesis
Kimmich, D (2011). IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

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