M.  Afifi, Derpanis, K. G., Ommer, B., and Brown, M. S., ?Learning Multi-Scale Photo Exposure Correction?, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

M.  Haußmann, Gerwinn, S., Look, A., Rakitsch, B., and Kandemir, M., ?Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes?, International Conference on Artificial Intelligence and Statistics , vol. PMLR 130. pp. 478-486, 2021.

S.  Friman, ?Laboratory investigations of concentration and wind profiles close to the wind-driven wavy water surface?, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, Heidelberg, 2020.

R.  Hühnerbein, Savarino, F., Petra, S., and Schnörr, C., ?Learning Adaptive Regularization for Image Labeling Using Geometric Assignment?, in Proc. SSVM, 2019.

R.  Hühnerbein, Savarino, F., Petra, S., and Schnörr, C., ?Learning Adaptive Regularization for Image Labeling Using Geometric Assignment?, preprint: arXiv, 2019.

T.  Leistner, Schilling, H., Mackowiak, R., Gumhold, S., and Rother, C., ?Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift?, in Proceedings - 2019 International Conference on 3D Vision, 3DV 2019, 2019, pp. 249?257.

E.  Kirschbaum, Haußmann, M., Wolf, S., Sonntag, H., Schneider, J., Elzoheiry, S., Kann, O., Durstewitz, D., and Hamprecht, F. A., ?LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos?, ICLR. Proceedings. 2019.

W.  Li, Hosseini Jafari, O., and Rother, C., ?Localizing Common Objects Using Common Component Activation Map?, 2019.

F.  Schimmel, ?Learnability of Approximated Graph Cut Segmentation?, Heidelberg University, 2018.

E.  Brachmann and Rother, C., ?Learning Less is More - 6D Camera Localization via 3D Surface Regression?, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2018, pp. 4654?4662.

M.  Weiler, Hamprecht, F. A., and Storath, M., ?Learning Steerable Filters for Rotation Equivariant CNNs?, CVPR. Proceedings. pp. 849-858, 2018.

O.  Ghori, Mackowiak, R., Bautista, M., Beuter, N., Drumond, L., Diego, F., and Ommer, B., ?Learning to Forecast Pedestrian Intention from Pose Dynamics?, in Intelligent Vehicles, IEEE, 2018, 2018.

L.  Schott, ?Learned Watershed Algorithm: End-to-End Learning of Seeded Segmentation?, Heidelberg University, 2017.

S.  Wolf, Schott, L., Köthe, U., and Hamprecht, F. A., ?Learned Watershed: End-to-End Learning of Seeded Segmentation?, ICCV. pp. 2030-2038, 2017.

M.  Weiler, ?Learning Steerable Filters for Rotation Equivariant Convolutional Neural Networks?, Heidelberg University, 2017.

J.  Kruse, Rother, C., Schmidt, U., and Dresden, T. U., ?Learning to Push the Limits of Efficient FFT-based Image Deconvolution - Supplemental Material?, 2017.

J.  Kruse, Rother, C., and Schmidt, U., ?Learning to Push the Limits of Efficient FFT-Based Image Deconvolution?, in Proceedings of the IEEE International Conference on Computer Vision, 2017, vol. 2017-Octob, pp. 4596?4604.

M.  Bautista, Fuchs, P., and Ommer, B., ?Learning Where to Drive by Watching Others?, Proceedings of the German Conference Pattern Recognition, vol. 1. Springer-Verlag, Basel, 2017.

E.  Bodnariuc, Petra, S., Schnörr, C., and Voorneveld, J., ?A Local Spatio-Temporal Approach to Plane Wave Ultrasound Particle Image Velocimetry?, in Proc. GCPR, 2017.

F.  Rathke, Desana, M., and Schnörr, C., ?Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans?, MICCAI. Proceedings. pp. 177-184, 2017.

F.  Rathke, Desana, M., and Schnörr, C., ?Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans?, in Proc. MICCAI, 2017.

B.  Brattoli, Büchler, U., Wahl, A. - S., Schwab, M. E., and Ommer, B., ?LSTM Self-Supervision for Detailed Behavior Analysis?, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

M.  Schiegg, Diego, F., and Hamprecht, F. A., ?Learning Diverse Models: The Coulomb Structured Support Vector Machine?, ECCV. Proceedings, vol. LNCS 9907. Springer, pp. 585-599, 2016.

M.  von Borstel, ?Learning to Count from Weak Supervision?, University of Heidelberg, 2016.

M.  Diebold, ?Light-Field Imaging and Heterogeneous Light Fields?, vol. Dissertation. IWR, Univ. Heidelberg, 2016.

P.  Pinggera, Ramos, S., Gehrig, S., Franke, U., Rother, C., and Mester, R., ?Lost and found: Detecting small road hazards for self-driving vehicles?, in IEEE International Conference on Intelligent Robots and Systems, 2016, vol. 2016-Novem, pp. 1099?1106.

A.  Krull, Brachmann, E., Michel, F., Yang, M. Ying, Gumhold, S., and Rother, C., ?Learning analysis-by-synthesis for 6d pose estimation in RGB-D images?, in Proceedings of the IEEE International Conference on Computer Vision, 2015, vol. 2015 Inter, pp. 954?962.

J.  Funke, Hamprecht, F. A., and Zhang, C., ?Learning to Segment: Training Hierarchical Segmentation under a Topological Loss?, in MICCAI. Proceedings, Part III, 2015, vol. 9351, pp. 268-275.

B.  Krolla, Diebold, M., and Stricker, D., ?Light Field from Smartphone-Based Dual Video?, in Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II, Cham: Springer International Publishing, 2015, pp. 600?610.

M.  Diebold, Blum, O., Gutsche, M., Wanner, S., Garbe, C. S., Baker, H., and Jähne, B., ?Light-field camera design for high-accuracy depth estimation?, Videometrics, Range Imaging, and Applications XIII. 2015.

M.  Diebold, Blum, O., Gutsche, M., Wanner, S., Garbe, C., Baker, H., and Jähne, B., ?Light-field camera design for high-accuracy depth estimation?, in Videometrics, Range Imaging, and Applications XIII, 2015.

M.  Hoai, Torresani, L., De La Torre, F., and Rother, C., ?Learning discriminative localization from weakly labeled data?, in Pattern Recognition, 2014, vol. 47, pp. 1523?1534.

B.  Antic and Ommer, B., ?Learning Latent Constituents for Recognition of Group Activities in Video?, in Proceedings of the European Conference on Computer Vision (ECCV) (Oral), 2014, p. 33--47.

T.  Kröger, ?Learning-based Segmentation for Connectomics?. University of Heidelberg, 2014.

M.  Bopp, ?Luft- und wasserseitige Strömungsverhältnisse im ringförmigen Heidelberger Wind-Wellen-Kanal (Aeolotron)?, Institut für Umweltphysik, Universität Heidelberg, Germany, 2014.

M.  Bopp, ?Luft- und wasserseitige Strömungsverhältnisse im ringförmigen Heidelberger Wind-Wellen-Kanal (Aeolotron)?, Institut für Umweltphysik, Universität Heidelberg, Germany, 2014.

K. E.  Krall, ?Laboratory Investigations of Air-Sea Gas Transfer under a Wide Range of Water Surface Conditions?, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2013.

R.  Walecki, ?Large-Scale Automatic Reconstruction of Myelianated Axons and Detection of the Nodes of Ranvier?, University of Heidelberg, 2013.

L.  Fiaschi, ?Learning Based Biological Image Analysis?. University of Heidelberg, 2013.

J.  Jancsary, Nowozin, S., and Rother, C., ?Learning convex QP relaxations for structured prediction?, in 30th International Conference on Machine Learning, ICML 2013, 2013, pp. 1952?1960.

F.  Diego and Hamprecht, F. A., ?Learning Multi-Level Sparse Representation?, in NIPS. Proceedings, 2013.

F.  Diego and Hamprecht, F. A., ?Learning Multi-Level Sparse Representation for Identifying Neuronal Activity?, in Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS). Book of Abstracts., 2013.

T.  Kröger, Mikula, S., Denk, W., Köthe, U., and Hamprecht, F. A., ?Learning to Segment Neurons with Non-local Quality Measures?, in MICCAI 2013. Proceedings, part II, 2013, vol. 8150, pp. 419-427.

B.  Antic, Milbich, T., and Ommer, B., ?Less is More: Video Trimming for Action Recognition?, in Proceedings of the IEEE International Conference on Computer Vision, Workshop on Understanding Human Activities: Context and Interaction, 2013, p. 515--521.

B.  Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., ?The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models?, in ECCV 2012, 2012.

B.  Andres, Kappes, J. Hendrik, Beier, T., Köthe, U., and Hamprecht, F. A., ?The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models?, in ECCV 2012, 2012.

B.  Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., ?The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models?, in Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}, 2012.

P.  Yarlagadda, Eigenstetter, A., and Ommer, B., ?Learning Discriminative Chamfer Regularization?, in BMVC, 2012, p. 1--11.

L.  Fiaschi, Nair, R., Köthe, U., and Hamprecht, F. A., ?Learning to Count with Regression Forest and Structured Labels?, ICPR 2012. Proceedings, pp. 2685-2688, 2012.

X.  Lou and Hamprecht, F. A., ?Learning to Segment Dense Cell Nuclei with Shape Prior?, CVPR 2012. Proceedings, pp. 1012-1018, 2012.

C.  Sommer, Fiaschi, L., Hamprecht, F. A., and Gerlich, D., ?Learning-based Mitotic Cell Detection in Histopathological Images?, ICPR 2012. Proceedings, pp. 2306-2309, 2012.

J.  Jancsary, Nowozin, S., and Rother, C., ?Loss-specific training of non-parametric image restoration models: A new state of the art?, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7578 LNCS, pp. 112?125.

J.  Jancsary, Nowozin, S., and Rother, C., ?Loss-specific training of non-parametric image restoration models: A new state of the art?, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7578 LNCS, pp. 112?125.

K. E.  Richter and Jähne, B., ?A laboratory study of the Schmidt number dependency of air-water gas transfer?, in Gas Transfer at Water Surfaces 2010, 2011, p. 322--332.

U.  Schimpf, Nagel, L., and Jähne, B., ?Lock-in thermography at the ocean surface: a local and fast method to investigate heat and gas exchange between ocean and atmosphere?, in DPG Frühjahrstagung Dresden, Fachverband Umweltphysik, 2011.

B.  Andres, Kappes, J. H., Köthe, U., and Hamprecht, F. A., ?The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search?, ArXiv e-prints, 2010.

H.  Nickisch, Rother, C., Kohli, P., and Rhemann, C., ?Learning an Interactive Segmentation System - Supplemental Material?, 2010.

M.  Jehle, Sommer, C., and Jähne, B., ?Learning of Optimal Illumination for Material Classification?, in Proceedings of the 32nd DAGM Symposium on Pattern Recognition, Darmstadt, Germany, 2010, pp. 563-572.

M.  Jehle, Sommer, C., and Jähne, B., ?Learning of optimal illumination for material classification?, in Pattern Recognition, 2010, vol. 6376, p. 563--572.

B.  Ommer and Buhmann, J. M., ?Learning the Compositional Nature of Visual Object Categories for Recognition?, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, p. 501--516, 2010.

J.  Fehr, ?Local Rotation Invariant Patch Descriptors for 3D Vector Fields?, Pattern Recognition, International Conference on, Istanbul, Turkey, August 23-26, 2010, pp. 1381-1384, 2010.

J.  Fehr and Burkhardt, H., ?Local Rotation Invariant Patch Descriptors for 3D Vector Fields?, in to be submitted, 2009.

A.  Haja, Jähne, B., and Abraham, S., ?Localization accuracy of region detectors?, in Proceedings CVPR'08, 2008.

B.  Ommer and Buhmann, J. M., ?Learning the Compositional Nature of Visual Objects?, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2007, p. 1--8.

V.  Lempitsky, Rother, C., and Blake, A., ?LogCut - Efficient graph cut optimization for markov random fields?, in Proceedings of the IEEE International Conference on Computer Vision, 2007.

D.  Withopf and Jähne, B., ?Learning algorithm for real-time vehicle tracking?, in Proc. IEEE Intelligent Transportation Systems Conference ITSC '06, 2006, p. 516--521.

B.  Ommer and Buhmann, J. M., ?Learning Compositional Categorization Models?, in Proceedings of the European Conference on Computer Vision, 2006, vol. 3953, p. 316--329.

M.  Bergtholdt, Kappes, J. H., and Schnörr, C., ?Learning of Graphical Models and Efficient Inference for Object Class Recognition?, in Proc. DAGM 2006, 2006, vol. 375-388, pp. 375-388.

M.  Heiler and Schnörr, C., ?Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming?, J. Mach. Learning Res., vol. 7, pp. 1385?1407, 2006.

B.  Ommer, Sauter, M., and M., B. J., ?Learning Top-Down Grouping of Compositional Hierarchies for Recognition?, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Workshop on Perceptual Organization in Computer Vision, 2006, p. 194--194.

M.  Heiler and Schnörr, C., ?Learning Sparse Image Codes by Convex Programming?, in Proc. Tenth IEEE Int. Conf. Computer Vision (ICCV'05), Beijing, China, 2005, pp. 1667-1674.

A.  Bruhn, Weickert, J., and Schnörr, C., ?Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods?, vol. 61, pp. 211-231, 2005.

S.  Weber, Schüle, T., Schnörr, C., and Hornegger, J., ?A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections?, Methods of Information in Medicine, vol. 43, pp. 320?326, 2004.

C.  Rother, ?Linear Multi-View Reconstruction for Translating Cameras?, Nada.Kth.Se, 2003.

C.  Rother, ?Linear multi-view reconstruction of points, lines, planes and cameras using a reference plane?, in Proceedings of the IEEE International Conference on Computer Vision, 2003, vol. 2, pp. 1210?1217.

S.  Weber, Schüle, T., Schnörr, C., and Hornegger, J., ?A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections?, in Bildverarbeitung für die Medizin 2003, 2003, pp. 41?45.

S.  Weber, Schnörr, C., and Hornegger, J., ?A Linear Programming Relaxation for Binary Tomography with Smoothness Priors?, in Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'03), Palermo, Italy, 2003.

H.  Scharr and Küsters, R., ?A linear model for simultaneous estimation of 3D motion and depth?, in Proceedins of IEEE Workshop on Motion and Video Computing 2002, Orlando, 2002.

C.  Rother and Carlsson, S., ?Linear multi view reconstruction and camera recovery using a reference plane?, International Journal of Computer Vision, vol. 49, pp. 117?141, 2002.

C.  Rother and Carlsson, S., ?Linear multi view reconstruction with missing data?, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2002, vol. 2351, pp. 209?324.

H.  Spies, Dierig, T., Garbe, C. S., and Würtz, R. P., ?Local models for dynamic processes in image sequences?, in Dynamic Perception, 2002, p. 59--64.

C.  Rother and Carlsson, S., ?Linear multi view reconstruction and camera recovery?, in Proceedings of the IEEE International Conference on Computer Vision, 2001, vol. 1, pp. 42?49.

D.  Cremers, Schnörr, C., Weickert, J., and Schellewald, C., ?Learning Translation Invariant Shape Knowledge for Steering Diffusion-Snakes?, in 3rd Workshop on Dynamic Perception, Berlin, Germany, 2000, vol. 9, pp. 117?122.

B.  Jähne, Jähne, B., and Haußecker, H., ?Local averaging?, Handbook of Computer Vision and Applications. Volume II: Signal Processing and Pattern Recognition. Academic Press, p. 153--174, 1999.

B.  Jähne, Jähne, B., and Haußecker, H., ?Local structure?, Handbook of Computer Vision and Applications. Volume II: Signal Processing and Pattern Recognition. Academic Press, p. 209--238, 1999.

T.  Münsterer and Jähne, B., ?LIF measurements of concentration profiles in the aqueous mass boundary layer?, Exp. Fluids, vol. 25, p. 190--196, 1998.

W.  Peckar, Schnörr, C., Rohr, K., Stiehl, H. ?S., and Spetzger, U., ?Linear and Incremental Estimation of Elastic Deformations in Medical Registration Using Prescribed Displacements?, Machine Graphics & Vision, vol. 7, pp. 807?829, 1998.

P.  Geißler and Jähne, B., ?Laboratory and inshore measurements of bubble size distributions?, in Proc. Natural Physical Processes associated with Sea Surface Sound, Southampton, July 21--24, 1997, 1997, p. 147--154.

R.  Fitzenberger, ?Lokale Transformationsmethoden zur Auswertung von Wellenneigungsbildern der Wasseroberfläche im Bereich kleinskaliger Oberflächenwellen?, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, 1997.

F.  Hering, ?Lagrangesche Untersuchungen des Strömungsfeldes unterhalb der wellenbewegten Wasseroberfläche mittels Bildfolgenanalyse?. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1996.

T.  Münsterer, ?LIF Investigation of the Mechanisms Controlling Air--Water Mass Transfer at a Free Interface?. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1996.

R.  Bremeyer, ?Lokale Orientierung zur Auswertung von Streakbildern?, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, 1995.

M.  Beyer, Jähne, B., and Melville, W. K., ?Laboratory studies of long-wave/short-wave interaction using wavelet analysis of space-time images?, in Proc. 2nd Inter. Conf. on Air-Sea Interaction and on Meteorology and Oceanography of the Coastal Zone, Lisbon, 22.--27. September 1994, 1994.

T.  Münsterer and Jähne, B., ?A LIF technique for the measurement of concentration profiles in the aqueous mass boundary layer?, in Proc.\ 7th Intern.\ Symp.\ on Appl.\ of Laser Techn.\ to Fluid Mechanics, Lisbon, Portugal, July 11.--14. 1994, 1994, vol. II, p. 29.4.1--5.