Publications

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Brocke, M (2002). Statistical Image Sequence Processing for Temporal Change Detection. Proceedings of the 24th DAGM Symposium on Pattern Recognition. LNCS 2449 215--223
Broecker, W S, Ledwell, J R, Takahashi, T, Weiss, R, Merlivat, L, Memery, L, Jähne, B and Münnich, K O (1986). Isotopic versus micrometeorologic ocean CO$_2$ fluxes: A serious conflict. J. Geophys. Res. 91 10517--10528
Brosowsky, M (2017). Cluster Resolving For Animal Tracking: Multi Hypotheses Tracking With Part Based Model For Object Hypotheses Generation And Pose Estimation. University of Heidelberg
Bruhn, A, Weickert, J and Schnörr, C (2005). Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods. IJCV. 61 211-231
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
Bruhn, A, Weickert, J and Schnörr, C (2002). Combining the Advantages of Local and Global Optic Flow Methods. Pattern Recognition, Proc.~24th DAGM Symposium. Springer. 2449 454--462
Bruhn, A, Weickert, J, Feddern, C, Kohlberger, T and Schnörr, C (2003). Real-Time Optic Flow Computation with Variational Methods. Proc.~Computer Analysis of Images and Patterns (CAIP'03). Springer. 2756 222-229
Bruhn, A, Weickert, J, Kohlberger, T and Schnörr, C (2005). Discontinuity-Preserving Computation of Variational Optic Flow in Real-Time. Scale-Space 2005. Springer. 3459 279--290
Bruhn, A, Jakob, T, Fischer, M, Weickert, J, Brüning, U and Schnörr, C (2004). High performance cluster computing with 3-D nonlinear diffusion filters. Real-Time Imaging. 10 41--51
Bruhn, A, Weickert, J, Kohlberger, T and Schnörr, C (2006). A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods. Int.~J.~Computer Vision. 70 257-277PDF icon Technical Report (447.65 KB)
Bruhn, A, Jakob, T, Fischer, M, Kohlberger, T, Weickert, J, Brüning, U and Schnörr, C (2002). Designing 3--D Nonlinear Diffusion Filters for High Performance Cluster Computing. Pattern Recognition, Proc.~24th DAGM Symposium. Springer. 2449 290--297
Bruhn, A, Weickert, J, Feddern, C, Kohlberger, T and Schnörr, C (2003). Variational Optic Flow Computation In Real-Time. Dept.~Math.~and Comp.~Science
Brunswig, F (1992). Strukturanalyse Von Gletschereis Und Baumringen Mittels Digitaler Bildanalyse. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Büchler, U, Brattoli, B and Ommer, B (2018). Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning. Proceedings of the European Conference on Computer Vision (ECCV). (UB and BB contributed equally), Munich, GermanyPDF icon Article (5.34 MB)PDF icon buechler_eccv18_poster.pdf (1.65 MB)
Bühl, M and Hamprecht, F A (1998). Theoretical Investigation of NMR Chemical Shifts and Reactivities of Oxovanadium (V) Compounds. Journal of Computational Chemistry. 19 113-122
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Cali, C, Baghabra, J, Boges, D J, Holst, G R, Kreshuk, A, Hamprecht, F A, Srinivasan, M, Lehväslaiho, H and Magistretti, P J (2015). Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues. Journal of Comparative Neurology. 524 23-38
Jähne, B and Jähne, B (1991). Evaluation of a two-scale model using extensive radar backscatter and wave measurements in a large wind-wave flume. Proceedings IGARSS '91. 2 885--888
Carlsohn, M F, Menze, B H, Kelm, B M, Hamprecht, F A, Kercek, A, Leitner, R and Polder, G (2006). Color image processing. CRC Press. 7(17) 393-419
Carstens, H (1998). Ein Skalenraumverfahren Zur Orts/wellenzahl-Raum-Analyse Winderzeugter Wasserwellen. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg
Cavallo, A (2002). Four dimensional particle tracking in biological dynamic processes. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg. http://www.ub.uni-heidelberg.de/archiv/2471/
Cerrone, L, Zeilmann, A and Hamprecht, F A (2019). End-to-End Learned Random Walker for Seeded Image Segmentation. CVPR. Proceedings, in press
Cerrone, L (2018). Deep End-To-End Learning Of A Diffusion Process For Seeded Image Segmentation. Heidelberg University
Cremers, D, Sochen, N and Schnörr, C (2003). Towards Recognition-Based Variational Segmentation Using Shape Priors and Dynamic Labeling. Scale Space Methods in Computer Vision. Springer. 2695 388--400PDF icon Technical Report (451.82 KB)
Cremers, D and Schnörr, C (2002). Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization. Pattern Recognition, Proc.~24th DAGM Symposium. Springer. 2449 472--480
Cremers, D, Schnörr, C, Weickert, J and Schellewald, C (2000). Diffusion Snakes Using Statistical Shape Knowledge. Proc.~Algebraic Frames for the Perception-Action Cycle. Springer. 1888 164--174
Cremers, D, Kohlberger, T and Schnörr, C (2003). Shape Statistics in Kernel Space for Variational Image Segmentation. Pattern Recognition. 36 1929--1943PDF icon Technical Report (1.67 MB)
Cremers, D, Tischhäuser, F, Weickert, J and Schnörr, C (2002). Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford--Shah functional. Int.~J.~Computer Vision. 50 295--313
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. 9 117--122
Cremers, D, Kohlberger, T and Schnörr, C (2001). Nonlinear Shape Statistics via Kernel Spaces. Mustererkennung 2001. Springer. 2191 269--276PDF icon Technical Report (324.55 KB)
Cremers, D, Sochen, N and Schnörr, C (2006). Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. IJCV. 66 67-81
Cremers, D, Schnörr, C and Weickert, J (2001). Diffusion--Snakes: Combining Statistical Shape Knowledge and Image Information in a Variational Framework. IEEE First Workshop on Variational and Level Set Methods in Computer Vision. IEEE Comp.~Soc. 237--244
Cremers, D, Kohlberger, T and Schnörr, C (2002). Nonlinear Shape Statistics in Mumford-Shah Based Segmentation. Computer Vision -- ECCV 2002). Springer Verlag. 2351 93--108PDF icon Technical Report (636.58 KB)
Cremers, D, Sochen, N and Schnörr, C (2004). Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation. Computer Vision -- ECCV 2004. Springer. 3024 74-86
Cremers, D and Schnörr, C (2003). Statistical Shape Knowledge in Variational Motion Segmentation. Image and Vision Comp. 21 77-86
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Daume, D (2010). Fusion Von Midwave-Infrared- Und Longwave-Infrared-Wärmebildgeräten Zur Klassifizierung Von Flugobjekten. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg

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