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Publications

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Author [ Title(Asc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
D
T. Kohlberger, Schnörr, C., Bruhn, A., and Weickert, J., “Domain Decomposition for Variational Optical Flow Computation”, Dept. Math. and Comp. Science, University of Mannheim, Germany, 07/2003, 2003.
T. Kohlberger, Schnörr, C., Bruhn, A., and Weickert, J., “Domain Decomposition for Parallel Variational Optical Flow Computation”, in Pattern Recognition, Proc. 25th DAGM Symposium, 2003, vol. 2781, pp. 196–203.
S. Kraus, “DOASIS a framework design for DOAS”. Technische Informatik, Univ. Mannheim, 2006.
S. Kraus, “DOASIS a framework design for DOAS”. Technische Informatik, Univ.\ Mannheim, 2006.
A. Sellen, Fogg, A., Aitken, M., Hodges, S., Rother, C., and Wood, K., “Do life-logging technologies support memory for the past? An experimental study using sensecam”, in Conference on Human Factors in Computing Systems - Proceedings, 2007, pp. 81–90.
A. Sanakoyeu, Tschernezki, V., Büchler, U., and Ommer, B., “Divide and Conquer the Embedding Space for Metric Learning”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2019.
V. Uhlmann, Haubold, C., Hamprecht, F. A., and Unser, M., “Diverse Shortest Paths for Bioimage Analysis”, Bioinformatics, pp. 1-3, 2017.
C. Haubold, Uhlmann, V., Unser, M., and Hamprecht, F. A., “Diverse M-best Solutions by Dynamic Programming”, GCPR. Proceedings, vol. LNCS 10496. Springer, pp. 255-267, 2017.
T. Milbich, Roth, K., Bharadhwaj, H., Sinha, S., Bengio, Y., Ommer, B., and Cohen, J. Paul, “DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning”, IEEE European Conference on Computer Vision (ECCV). 2020.
A. Stahl, Ruhnau, P., and Schnörr, C., “A Distributed Parameter Approach to Dynamic Image Motion”, in ECCV 2006, International Workshop on The Representation and Use of Prior Knowledge in Vision, 2006.PDF icon Technical Report (1.24 MB)
P. Esser, Rombach, R., and Ommer, B., “A Disentangling Invertible Interpretation Network for Explaining Latent Representations”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2020.PDF icon Article (13.07 MB)
P. Sorrenson, Rother, C., and Köthe, U., “Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)”, in Intl. Conf. Learning Representations (ICLR), 2020.PDF icon PDF (2.43 MB)
U. Schmidt, Rother, C., Nowozin, S., Jancsary, J., and Roth, S., “Discriminative Non-blind Deblurring”, 2013.
T. Schüle, Schnörr, C., Weber, S., and Hornegger, J., “Discrete Tomography By Convex-Concave Regularization and D.C. Programming”, Discr. Appl. Math., vol. 151, pp. 229-243, 2005.
T. Schüle, Schnörr, C., Weber, S., and Hornegger, J., “Discrete Tomography By Convex-Concave Regularization and D.C. Programming”, Dept. Math. and Comp. Science, University of Mannheim, Germany, 15, 2003.
M. Zisler, Petra, S., Schnörr, C., and Schnörr, C., “Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints”, in Proc. GCPR, 2016.
J. Yuan, Schnörr, C., and Mémin, E., “Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation”, J.~Math.~Imag.~Vision, vol. 28, pp. 67-80, 2007.PDF icon Technical Report (752.44 KB)
J. Yuan, Ruhnau, P., Mémin, E., and Schnörr, C., “Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation”, in Scale-Space 2005, 2005, vol. 3459, pp. 267–278.
B. Savchynskyy, “Discrete Graphical Models — An Optimization Perspective”, Foundations and Trends® in Computer Graphics and Vision, vol. 11, pp. 160–429, 2019.
B. X. Kausler, Schiegg, M., Andres, B., Lindner, M., Köthe, U., Leitte, H., Wittbrodt, J., Hufnagel, L., and Hamprecht, F. A., “A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness”, in ECCV 2012. Proceedings, 2012, vol. 7574, pp. 144-157.PDF icon Technical Report (809.07 KB)
J. Lellmann, Lellmann, B., Widmann, F., and Schnörr, C., “Discrete and Continuous Models for Partitioning Problems”, Int.~J.~Comp.~Visionz, vol. 104, pp. 241-269, 2013.PDF icon Technical Report (4.74 MB)
S. Damrich, “Discovering Structure without Labels”, Heidelberg University. 2022.
A. Bruhn, Weickert, J., Kohlberger, T., and Schnörr, C., “Discontinuity-Preserving Computation of Variational Optic Flow in Real-Time”, in Scale-Space 2005, 2005, vol. 3459, pp. 279–290.
K. Lerch, “Discontinuity Preserving Filtering of Spectral Images”, University of Heidelberg, 2006.
E. Kirschbaum, Bailoni, A., and Hamprecht, F. A., “DISCo: Deep Learning, Instance Segmentation, and Correlations for Cell Segmentation in Calcium Imaging”, MICCAI. Proceedings. pp. 151-162, 2020.
E. Fita, Damrich, S., and Hamprecht, F. A., “Directed Probabilistic Watershed”, NeurIPS. Proceedings, vol. 34. 2021.PDF icon Technical Report (957.78 KB)
M. Jehle, Jähne, B., and Kertzscher, U., “Direct estimation of the wall shear rate using parametric motion models in 3D”, in Proceedings of the 28th DAGM Symposium on Pattern Recognition, 2006, vol. 4174, p. 434--443.
H. Scharr, “Digitale Bildverarbeitung und Papier Texturanalyse mittels Pyramiden und Grauwertstatistiken am Beispiel der Papierformation”, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1996.
B. Jähne, Digitale Bildverarbeitung und Bildgewinnung. Springer Vieweg, 2012.
B. Jähne, Digitale Bildverarbeitung, 6th ed. Springer, 2005.
B. Jähne, Digitale Bildverarbeitung, Fünfte. Springer Verlag, 2002.
B. Jähne, Digitale Bildverarbeitung, 4th ed. Springer, 1997.
B. Jähne, Digitale Bildverarbeitung, 3rd ed. Springer, 1993.
B. Jähne, Digitale Bildverarbeitung, 2nd ed. Springer, 1991.
B. Jähne, Digitale Bildverarbeitung. Springer, 1989.

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