All Publications

2018

Weiler, M, Hamprecht, F A and Storath, M (2018). Learning Steerable Filters for Rotation Equivariant CNNs. CVPR
Sanakoyeu, A, Bautista, M and Ommer, B (2018). Deep Unsupervised Learning of Visual Similarities. Pattern Recognition. 78. https://authors.elsevier.com/a/1WXUt77nKSb25 PDF icon PDF (8.35 MB)
Brachmann, E and Rother, C (2018). Learning Less is More - 6D Camera Localization via 3D Surface Regression. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 4654–4662. http://arxiv.org/abs/1711.10228
Kiechle, M, Storath, M, Weinmann, A and Kleinsteuber, M (2018). Model-based learning of local image features for unsupervised texture segmentation. IEEE Transactions on Image Processing. 27 1994-2007
Schilling, H, Diebold, M, Rother, C and Jähne, B (2018). Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 4530–4538
Kostrykin, L, Schnörr, C and Rohr, K (2018). Segmentation of Cell Nuclei Using Intensity-Based Model Fitting and Sequential Convex Programming. Proc. ISBI
Zern, A, Rohr, K and Schnörr, C (2018). Geometric Image Labeling with Global Convex Labeling Constraints. EMMCVPR. 10746 533–547
Rathke, F and Schnörr, C (2018). Fast Multivariate Log-Concave Density Estimation. preprint: arXiv. https://arxiv.org/pdf/1805.07272.pdf
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM J. Imaging Science. 11 1317–1362. https://epubs.siam.org/doi/abs/10.1137/17M1150669
Zern, A, Zisler, M, Aström, F, Petra, S and Schnörr, C (2018). Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment. GCPR
Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2018). Geometric Numerical Integration of the Assignment Flow. preprint: arXiv. https://arxiv.org/abs/1810.06970
Storath, M and Weinmann, A (2018). Fast median filtering for phase or orientation data. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40 639–652PDF icon Technical Report (7.32 MB)

2017

Storath, M, Brandt, C, Hofmann, M, Knopp, T, Salamon, J, Weber, A and Weinmann, A (2017). Edge preserving and noise reducing reconstruction for magnetic particle imaging. IEEE Transactions on Medical Imaging. 36 74 - 85PDF icon Technical Report (1.43 MB)
Balluff, B, Hanselmann, M and Heeren, R M A (2017). Mass spectrometry imaging for the investigation of intratumor heterogeneity. Advances in Cancer Research. Elsevier. 134 201-230
Storath, M, Weinmann, A and Unser, M (2017). Jump-penalized least absolute values estimation of scalar or circle-valued signals. Information and Inference. 6 225–245PDF icon Technical Report (3.4 MB)
Beier, T, Pape, C, Rahaman, N, Prange, T, Berg, S, Bock, D, Cardona, A, Knott, G W, Plaza, S M, Scheffer, L K, Köthe, U, Kreshuk, A and Hamprecht, F A (2017). Multicut brings automated neurite segmentation closer to human performance. Nature Methods. 14 101-102. http://rdcu.be/oVDQ
Haltebourg, C (2017). Modeling of Heat Exchange Across the Ocean Surface as Measured by Active Thermography. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg. Dissertation
Ufer, N and Ommer, B (2017). Deep Semantic Feature Matching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)PDF icon article (8.88 MB)
Brattoli, B, Büchler, U, Wahl, A - S, Schwab, M E and Ommer, B (2017). LSTM Self-Supervision for Detailed Behavior Analysis. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). (BB and UB contributed equally)PDF icon Article (8.75 MB)
Haußmann, M, Hamprecht, F A and Kandemir, M (2017). Variational Bayesian Multiple Instance Learning with Gaussian Processes. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 6570-6579PDF icon Technical Report (1.29 MB)
Haller, A (2017). Interactive Watershed Based Segmentation For Biological Images. University of Heidelberg
Kunz, J (2017). Active Thermography as a Tool for the Estimation of Air-Water Transfer Velocities. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg. Dissertation
Flothow, L (2017). Bubble Characteristics From Breaking Waves In Fresh Water And Simulated Seawater. Institut für Umweltphysik, Universität Heidelberg, Germany
Rennebaum, A (2017). Spatio-Temporal Properties Of The Initial Wave Formation Phase At The Aeolotron. Institut für Umweltphysik, Universität Heidelberg, Germany
Holtmann, L Gerhard (2017). Aufbau Eines Aktiven Thermographiesystems Zur Messung Des Geschwindigkeitsgradienten In Der Windgetriebenen Wasserseitigen Viskosen Grenzschicht. Institut für Umweltphysik, Universität Heidelberg, Germany
Vianello, A (2017). Robust 3D Surface Reconstruction from Light Fields. IWR, Univ. Heidelberg. Dissertation
Vianello, A, Manfredi, G, Diebold, M and Jähne, B (2017). 3D reconstruction by a combined structure tensor and Hough transform light field approach. tm - Technisches Messen
von Schmude, N (2017). Visual Localization with Lines. IWR, Univ. Heidelberg. Dissertation
Schilling, H, Diebold, M, Gutsche, M and Jähne, B (2017). On the design of a fractal calibration pattern for improved camera calibration. tm - Technisches Messen. 84 440–451
Krause, G (2017). Correlation Of Performance And Entropy In Active Learning With Convolutional Neural Networks. Heidelberg University
Ulman, V, Maška, M, Magnusson, K E G, Ronneberger, O, Haubold, C, Harder, N, Matula, P, Matula, P, Svoboda, D, Radojevic, M, Smal, I, Rohr, K, Jaldén, J, Blau, H M, Dzyubachyk, O, Lelieveldt, B, Xiao, P, Li, Y, Cho, S - Y, Dufour, A, Olivo-Marin, J C, Reyes-Aldasoro, C C, Solis-Lemus, J A, Bensch, R, Brox, T, Stegmaier, J, Mikut, R, Wolf, S, Hamprecht, F A, Esteves, T, Quelhas, P, Demirel, Ö, Malström, L, Jug, F, Tomančák, P, Meijering, E, Muñoz-Barrutia, A, Kozubek, M and Ortiz-de-Solorzano, C (2017). An Objective Comparison of Cell Tracking Algorithms. Nature Methods. 14 1141-1152PDF icon Technical Report (4.24 MB)
Rathke, F, Desana, M and Schnörr, C (2017). Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans. MICCAI. Proceedings. 177-184PDF icon Technical Report (4.79 MB)
Hehn, T (2017). A Probabilistic Approach To Learn Complex Differentiable Split Functions In Decision Trees Using Gradient Ascent. Heidelberg University
Schott, L (2017). Learned Watershed Algorithm: End-To-End Learning Of Seeded Segmentation. Heidelberg University
Peter, S, Diego, F, Hamprecht, F A and Nadler, B (2017). Cost-efficient Gradient Boosting. NIPS, poster
Peter, S, Kirschbaum, E, Both, M, Campbell, L A, Harvey, B K, Heins, C, Durstewitz, D, Diego, F and Hamprecht, F A (2017). Sparse convolutional coding for neuronal assembly detection. NIPS, poster
Uhlmann, V, Haubold, C, Hamprecht, F A and Unser, M (2017). Diverse Shortest Paths for Bioimage Analysis. Bioinformatics. 1-3
Neigel, P (2017). Self-Similarity Based Detection Of Temporal Motifs In Multivariate Signals. Heidelberg University
Zisler, M, Savarino, F, Petra, S and Schnörr, C (2017). Gradient Flows on a Riemannian Submanifold for Discrete Tomography. Proc. GCPR
Weiler, M (2017). Learning Steerable Filters For Rotation Equivariant Convolutional Neural Networks. Heidelberg University

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