Publications

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A
Lenzen, F, Becker, F and Lellmann, J (2013). Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities. Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 2013. Springer. 54 371--398PDF icon Technical Report (702.08 KB)
Lenzen, F, Becker, F and Lellmann, J (2013). Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities. Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision SSVM. Springer. 7893 61-73
B
Petra, S, Schnörr, C, Becker, F and Lenzen, F (2013). B-SMART: Bregman-Based First-Order Algorithms for Non-Negative Compressed Sensing Problems. Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 2013. Springer. 7893 110-124PDF icon Technical Report (1.15 MB)
Petra, S, Schnörr, C, Becker, F and Lenzen, F (2013). B-SMART: Bregman-Based First-Order Algorithms for Non-Negative Compressed Sensing Problems. Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision SSVM. 110-124
C
Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2013). A class of quasi-variational inequalities for adaptive image denoising and decomposition. Computational Optimization and Applications. Springer Netherlands. 54 371-398. http://dx.doi.org/10.1007/s10589-012-9456-0PDF icon Technical Report (748.66 KB)
Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2013). A Class of Quasi-Variational Inequalities for Adaptive Image Denoising and Decomposition. Computational Optimization and Applications (COAP). 54 (2) 371-398
Lellmann, J, Kappes, J H, Yuan, J, Becker, F and Schnörr, C (2009). Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation. Scale Space and Variational Methods in Computer Vision (SSVM 2009). Springer. 5567 150-162PDF icon Technical Report (1.75 MB)
Lellmann, J, Kappes, J H, Yuan, J, Becker, F and Schnörr, C (2008). Convex Multi-Class Image Labeling By Simplex-Constrained Total Variation. IWR, University of Heidelberg. http://www.ub.uni-heidelberg.de/archiv/8759/PDF icon Technical Report (2.6 MB)
Lellmann, J, Kappes, J H, Yuan, J, Becker, F, Schnörr, C, Mórken, K and Lysaker, M (2009). Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation. Scale Space and Variational Methods in Computer Vision (SSVM 2009). Springer. 5567 150-162
Lellmann, J, Becker, F and Schnörr, C (2009). Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers. IEEE International Conference on Computer Vision (ICCV). 646 -- 653PDF icon Technical Report (930.18 KB)
Lellmann, J, Becker, F and Schnörr, C (2009). Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers. Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan. 646-653
D
Becker, F and Schnörr, C (2008). Decomposition of Quadratric Variational Problems. Pattern Recognition -- 30th DAGM Symposium. 5096 325--334
Becker, F and Schnörr, C (2008). Decomposition of Quadratric Variational Problems. Pattern Recognition -- 30th DAGM Symposium. Springer Verlag. 5096 325--334PDF icon Technical Report (1.29 MB)
Lenzen, F, Kim, K I, Schäfer, H, Nair, R, Meister, S, Becker, F and Garbe, C S (2013). Denoising Strategies for Time-of-Flight Data. Time-of-Flight Imaging: Algorithms, Sensors and Applications. Springer. 8200 24-25
Lenzen, F, Kim, K In, Schäfer, H, Nair, R, Meister, S, Becker, F and Garbe, C S (2013). Denoising Strategies for Time-of-Flight Data. Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications. Springer. 8200 25-45PDF icon Technical Report (961.62 KB)
O
Becker, F, Petra, S and Schnörr, C (2014). Optical Flow. Handbook of Mathematical Methods in Imaging. Springer
S
Berger, J, Neufeld, A, Becker, F, Lenzen, F and Schnörr, C (2015). Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations. Scale Space and Variational Methods in Computer Vision (SSVM 2015)
Berger, J, Neufeld, A, Becker, F, Lenzen, F and Schnörr, C (2015). Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations. Scale Space and Variational Methods in Computer Vision (SSVM 2015). Springer International Publishing. http://dx.doi.org/10.1007/978-3-319-18461-6_32PDF icon Technical Report (364.01 KB)
Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2015). Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. http://arxiv.org/abs/1507.06810
Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2015). Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. http://arxiv.org/abs/1507.06810PDF icon Technical Report (4.42 MB)
Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2017). {Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. J. Math. Imag. Vision. 58 102–129
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
Yuan, J, Schnörr, C, Steidl, G and Becker, F (2005). A Study of Non-Smooth Convex Flow Decomposition. Proc. Variational, Geometric and Level Set Methods in Computer Vision. Springer. 3752 1–12
V
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)
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, Yuan, J and Schnörr, C (2008). A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry. Pattern Recognition -- 30th DAGM Symposium. Springer Verlag. 5096 335--344PDF icon Technical Report (1.82 MB)
Becker, F, Wieneke, B, Yuan, J and Schnörr, C (2008). A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry. Pattern Recognition – 30th DAGM Symposium. Springer Verlag. 5096 335–344
Becker, F, Wieneke, B, Yuan, J and Schnörr, C (2008). A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry". Pattern Recognition -- 30th DAGM Symposium. 5096 335-344

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