Publications

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Jähne, B, Jähne, B and Haußecker, H (1999). Local structure. Handbook of Computer Vision and Applications. Volume II: Signal Processing and Pattern Recognition. Academic Press. 209--238
Bodnariuc, E, Petra, S, Schnörr, C and Voorneveld, J (2017). A Local Spatio-Temporal Approach to Plane Wave Ultrasound Particle Image Velocimetry. Proc. GCPR
Fehr, J (2010). Local Rotation Invariant Patch Descriptors for 3D Vector Fields. Pattern Recognition, International Conference on, Istanbul, Turkey, August 23-26, 2010. 1381-1384
Fehr, J and Burkhardt, H (2009). Local Rotation Invariant Patch Descriptors for 3D Vector Fields. to be submitted
Spies, H, Dierig, T, Garbe, C S and Würtz, R P (2002). Local models for dynamic processes in image sequences. Dynamic Perception. Aka GmbH. 59--64
Jähne, B, Jähne, B and Haußecker, H (1999). Local averaging. Handbook of Computer Vision and Applications. Volume II: Signal Processing and Pattern Recognition. Academic Press. 153--174
Weber, S, Schnörr, C and Hornegger, J (2003). A Linear Programming Relaxation for Binary Tomography with Smoothness Priors. Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'03). Palermo, Italy
Weber, S, Schüle, T, Schnörr, C and Hornegger, J (2004). A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections. Methods of Information in Medicine. 43 320–326
Weber, S, Schüle, T, Schnörr, C and Hornegger, J (2003). A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections. Bildverarbeitung für die Medizin 2003. Springer Verlag. 41–45
Rother, C (2003). Linear multi-view reconstruction of points, lines, planes and cameras using a reference plane. Proceedings of the IEEE International Conference on Computer Vision. 2 1210–1217. http://www.nada.kth.se/carstenr
Rother, C (2003). Linear Multi-View Reconstruction for Translating Cameras. Nada.Kth.Se. http://www.nada.kth.se/ carstenr/papers/paper_ssab03.pdf
Rother, C and Carlsson, S (2002). Linear multi view reconstruction with missing data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2351 209–324
Rother, C and Carlsson, S (2002). Linear multi view reconstruction and camera recovery using a reference plane. International Journal of Computer Vision. 49 117–141
Rother, C and Carlsson, S (2001). Linear multi view reconstruction and camera recovery. Proceedings of the IEEE International Conference on Computer Vision. 1 42–49
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
Peckar, W, Schnörr, C, Rohr, K, Stiehl, H –S and Spetzger, U (1998). Linear and Incremental Estimation of Elastic Deformations in Medical Registration Using Prescribed Displacements. Machine Graphics & Vision. 7 807–829
Diebold, M (2016). Light-Field Imaging and Heterogeneous Light Fields. IWR, Univ. Heidelberg. Dissertation
Diebold, M, Blum, O, Gutsche, M, Wanner, S, Garbe, C, Baker, H and Jähne, B (2015). Light-field camera design for high-accuracy depth estimation. Videometrics, Range Imaging, and Applications XIII. SPIE
Diebold, M, Blum, O, Gutsche, M, Wanner, S, Garbe, C S, Baker, H and Jähne, B (2015). Light-field camera design for high-accuracy depth estimation. Videometrics, Range Imaging, and Applications XIII
Krolla, B, Diebold, M and Stricker, D (2015). Light Field from Smartphone-Based Dual Video. Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II. Springer International Publishing, Cham. 600–610. http://dx.doi.org/10.1007/978-3-319-16181-5_46
Münsterer, T and Jähne, B (1994). A LIF technique for the measurement of concentration profiles in the aqueous mass boundary layer. Proc.\ 7th Intern.\ Symp.\ on Appl.\ of Laser Techn.\ to Fluid Mechanics, Lisbon, Portugal, July 11.--14. 1994. II 29.4.1--5
Münsterer, T and Jähne, B (1998). LIF measurements of concentration profiles in the aqueous mass boundary layer. Exp. Fluids. 25 190--196
Münsterer, (1996). LIF Investigation of the Mechanisms Controlling Air--Water Mass Transfer at a Free Interface. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Antic, B, Milbich, T and Ommer, B (2013). Less is More: Video Trimming for Action Recognition. Proceedings of the IEEE International Conference on Computer Vision, Workshop on Understanding Human Activities: Context and Interaction. IEEE. 515--521PDF icon Technical Report (984.89 KB)
Kirschbaum, E, Haußmann, M, Wolf, S, Sonntag, H, Schneider, J, Elzoheiry, S, Kann, O, Durstewitz, D and Hamprecht, F A (2019). LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos. ICLR. Proceedings
Kröger, (2014). Learning-based Segmentation for Connectomics. University of Heidelberg
Sommer, C, Fiaschi, L, Hamprecht, F A and Gerlich, D (2012). Learning-based Mitotic Cell Detection in Histopathological Images. ICPR 2012. Proceedings. 2306-2309PDF icon Technical Report (1.96 MB)
Bautista, M, Fuchs, P and Ommer, B (2017). Learning Where to Drive by Watching Others. Proceedings of the German Conference Pattern Recognition. Springer-Verlag, Basel. 1
Cremers, D, Schnörr, C, Weickert, J and Schellewald, C (2000). Learning Translation Invariant Shape Knowledge for Steering Diffusion-Snakes. 3rd Workshop on Dynamic Perception. Akad. Verlagsges., Berlin, Germany. 9 117–122
Ommer, B, Sauter, M and M., B J (2006). Learning Top-Down Grouping of Compositional Hierarchies for Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Workshop on Perceptual Organization in Computer Vision. IEEE. 194--194PDF icon Technical Report (358.98 KB)
Leistner, T, Schilling, H, Mackowiak, R, Gumhold, S and Rother, C (2019). Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift. Proceedings - 2019 International Conference on 3D Vision, 3DV 2019. 249–257. http://arxiv.org/abs/1909.09059 http://dx.doi.org/10.1109/3DV.2019.00036PDF icon PDF (8.94 MB)
Funke, J, Hamprecht, F A and Zhang, C (2015). Learning to Segment: Training Hierarchical Segmentation under a Topological Loss. MICCAI. Proceedings, Part III. Springer. 9351 268-275PDF icon Technical Report (2.92 MB)
Kröger, T, Mikula, S, Denk, W, Köthe, U and Hamprecht, F A (2013). Learning to Segment Neurons with Non-local Quality Measures. MICCAI 2013. Proceedings, part II. Springer. 8150 419-427PDF icon Technical Report (2.87 MB)
Lou, X and Hamprecht, F A (2012). Learning to Segment Dense Cell Nuclei with Shape Prior. CVPR 2012. Proceedings. 1012-1018PDF icon Technical Report (2.66 MB)
Kruse, J, Rother, C, Schmidt, U and Dresden, T U (2017). Learning To Push The Limits Of Efficient Fft-Based Image Deconvolution - Supplemental Material

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