HCI Logo
Heidelberg University Logo
IWR Logo

Publications

Export 1229 results:
Author Title Type [ Year(Desc)]
Filters: First Letter Of Last Name is S  [Clear All Filters]
2018
A. - S. Wahl, Erlebach, E., Brattoli, B., Büchler, U., Kaiser, J., Ineichen, V. B., Mosberger, A. C., Schneeberger, S., Imobersteg, S., Wieckhorst, M., Stirn, M., Schroeter, A., Ommer, B., and Schwab, M. E., “Early reduced behavioral activity induced by large strokes affects the efficiency of enriched environment in rats”, Sage Journals, vol. Journal of Cerebral Blood Flow & Metabolism, 2018.PDF icon 0271678x18777661.pdf (770.87 KB)
A. - S. Wahl, Erlebach, E., Brattoli, B., Büchler, U., Kaiser, J., Ineichen, V. B., Mosberger, A. C., Schneeberger, S., Imobersteg, S., Wieckhorst, M., Stirn, M., Schroeter, A., Ommer, B., and Schwab, M. E., “Early reduced behavioral activity induced by large strokes affects the efficiency of enriched environment in rats”, Sage Journals, vol. Journal of Cerebral Blood Flow & Metabolism, 2018.PDF icon 0271678x18777661.pdf (770.87 KB)
F. Draxler, Veschgini, K., Salmhofer, M., and Hamprecht, F. A., “Essentially No Barriers in Neural Network Energy Landscape”, ICML. Proceedings, vol. 80. p. 1308--1317, 2018.PDF icon Technical Report (685.93 KB)
S. Haller, Swoboda, P., and Savchynskyy, B., “Exact MAP-Inference by Confining Combinatorial Search With LP Relaxation”, in Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018, 2018.PDF icon 2018-02-02_aaai_dense_combilp.pdf (325.08 KB)
S. Haller, Swoboda, P., and Savchynskyy, B., “Exact MAP-Inference by Confining Combinatorial Search With LP Relaxation”, in Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018, 2018.PDF icon 2018-02-02_aaai_dense_combilp.pdf (325.08 KB)
M. Storath and Weinmann, A., “Fast median filtering for phase or orientation data”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 3, pp. 639–652, 2018.PDF icon Technical Report (7.32 MB)
F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, preprint: ArXiv, 2018.PDF icon Technical Report (3.54 MB)
F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, preprint: arXiv, 2018.
D. Fortun, Storath, M., Rickert, D., Weinmann, A., and Unser, M., “Fast Piecewise-Affine Motion Estimation Without Segmentation”, IEEE Transactions on Image Processing, vol. 27 , no. 11, pp. 5612 - 5624, 2018.
A. Zern, Rohr, K., and Schnörr, C., “Geometric Image Labeling with Global Convex Labeling Constraints”, in EMMCVPR, 2018, vol. 10746, pp. 533–547.
A. Zeilmann, Savarino, F., Petra, S., and Schnörr, C., “Geometric Numerical Integration of the Assignment Flow”, preprint: arXiv, 2018.
A. Zeilmann, Savarino, F., Petra, S., and Schnörr, C., “Geometric Numerical Integration of the Assignment Flow”, preprint: arXiv, 2018.
R. Hühnerbein, Savarino, F., Aström, F., and Schnörr, C., “Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment”, SIAM Journal on Imaging Sciences, vol. 11, no. 2, pp. 1317-1362, 2018.PDF icon Technical Report (2.62 MB)
R. Hühnerbein, Savarino, F., Aström, F., and Schnörr, C., “Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment”, SIAM Journal on Imaging Sciences, vol. 11, no. 2, pp. 1317-1362, 2018.PDF icon Technical Report (2.62 MB)
R. Hühnerbein, Savarino, F., Aström, F., and Schnörr, C., “Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment”, SIAM J. Imaging Science, vol. 11, pp. 1317–1362, 2018.
R. Hühnerbein, Savarino, F., Aström, F., and Schnörr, C., “Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment”, SIAM J. Imaging Science, vol. 11, pp. 1317–1362, 2018.
F. Schimmel, “Learnability of Approximated Graph Cut Segmentation”, Heidelberg University, 2018.
M. Weiler, Hamprecht, F. A., and Storath, M., “Learning Steerable Filters for Rotation Equivariant CNNs”, CVPR. Proceedings. pp. 849-858, 2018.PDF icon Technical Report (1.35 MB)
W. Erb, Weinmann, A., Ahlborg, M., Brandt, C., Bringout, G., Buzug, T. M., Frikel, J., Kaethner, C., Knopp, T., März, T., Möddel, M., Storath, M., and Weber, A., “Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging”, Inverse Problems, vol. 34, no. 5, 2018.
A. Shekhovtsov, Swoboda, P., and Savchynskyy, B., “Maximum Persistency via Iterative Relaxed Inference in Graphical Models”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, pp. 1668–1682, 2018.
A. Shekhovtsov, Swoboda, P., and Savchynskyy, B., “Maximum Persistency via Iterative Relaxed Inference in Graphical Models”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, pp. 1668–1682, 2018.
A. Shekhovtsov, Swoboda, P., and Savchynskyy, B., “Maximum Persistency via Iterative Relaxed Inference in Graphical Models”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, pp. 1668–1682, 2018.
M. Kiechle, Storath, M., Weinmann, A., and Kleinsteuber, M., “Model-based learning of local image features for unsupervised texture segmentation”, IEEE Transactions on Image Processing, vol. 27, no. 4, pp. 1994-2007, 2018.
S. Tourani, Shekhovtsov, A., Rother, C., and Savchynskyy, B., “MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, vol. 11208 LNCS, pp. 264–281.
S. Tourani, Shekhovtsov, A., Rother, C., and Savchynskyy, B., “MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, vol. 11208 LNCS, pp. 264–281.
L. Kostrykin, Schnörr, C., and Rohr, K., “Segmentation of Cell Nuclei Using Intensity-Based Model Fitting and Sequential Convex Programming”, in Proc. ISBI, 2018.
A. Sanakoyeu, Kotovenko, D., Lang, S., and Ommer, B., “A Style-Aware Content Loss for Real-time HD Style Transfer”, in Proceedings of the European Conference on Computer Vision (ECCV) (Oral), 2018.
K. Bredies, Holler, M., Storath, M., and Weinmann, A., “Total Generalized Variation for Manifold-valued Data”, SIAM Journal on Imaging Sciences, vol. 11, no. 3, pp. 1785 - 1848, 2018.
H. Schilling, Diebold, M., Rother, C., and Jähne, B., “Trust your Model: Light Field Depth Estimation with inline Occlusion Handling”, CVPR. Proceedings. 2018.PDF icon Technical Report (5.46 MB)
H. Schilling, Diebold, M., Rother, C., and Jähne, B., “Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2018, pp. 4530–4538.
A. Zern, Zisler, M., Aström, F., Petra, S., and Schnörr, C., “Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment”, GCPR. Proceedings. pp. 698-713, 2018.PDF icon Technical Report (5.23 MB)
A. Zern, Zisler, M., Aström, F., Petra, S., and Schnörr, C., “Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment”, in GCPR, 2018.
P. Esser, Sutter, E., and Ommer, B., “A Variational U-Net for Conditional Appearance and Shape Generation”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (short Oral), 2018.
2019
K. E. Krall, Smith, A. W., Takagaki, N., and Jähne, B., “Air–sea gas exchange at wind speeds up to 85 m/s”, Ocean Science, vol. 15, p. 1783-–1799, 2019.
C. Schnörr, “Assignment Flows”, Variational Methods for Nonlinear Geometric Data and Applications. Springer, 2019.

Pages