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P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Recognition and Analysis of Objects in Medieval Images”, in Proceedins of the Aian Conference on Computer Vision, Workshop on e-Heritage, 2010, p. 296--305.

Technical Report (2.76 MB)

S. Lang and Ommer, B., “Reconstructing Histories: Analyzing Exhibition Photographs with Computational Methods”, Arts, Computational Aesthetics, vol. 7, 64, no. 64, 2018.

arts-07-00064.pdf (4.6 MB)

S. Wanner and Goldlücke, B., “Reconstructing Reflective and Transparent Surfaces from Epipolar Plane Images”, Pattern Recognition. Springer, p. 1--10, 2013.

A. Monroy, Carque, B., and Ommer, B., “Reconstructing the Drawing Process of Reproductions from Medieval Images”, in Proceedings of the International Conference on Image Processing, 2011, p. 2974--2977.

Technical Report (2.43 MB)

A. Grützmann, “Reconstruction of Moving Surfaces of Revolution from Sparse 3-D Measurements using a Stereo Camera and Structured Light”. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg, 2009.

P. Vincent Gehler, Rother, C., Kiefel, M., Zhang, L., and Schölkopf, B., “Recovering intrinsic images with a global sparsity prior on reflectance”, in Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011, 2011.

S. Lang and Ommer, B., “Reflecting on How Artworks Are Processed and Analyzed by Computer Vision”, European Conference on Computer Vision (ECCV - VISART). Springer, 2018.

R. Nair, Fitzgibbon, A., Kondermann, D., and Rother, C., “Reflection modeling for passive stereo”, in Proceedings of the IEEE International Conference on Computer Vision, 2015, vol. 2015 Inter, pp. 2291–2299.

J. Esparza, Vepa, L., Helmle, M., and Jähne, B., “Registration of a multi-camera system with a 3D laser range finder”, in 9th Workshop Driver Assistance Systems (FAS2014), 26.-28.03.2014, Walting, 2014, p. 37--46.

J. Jancsary, Nowozin, S., Sharp, T., and Rother, C., “Regression Tree Fields An efficient, non-parametric approach to image labeling problems”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2012, pp. 2376–2383.

J. Jancsary, Nowozin, S., Sharp, T., and Rother, C., “Regression Tree Fields An efficient, non-parametric approach to image labeling problems”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2012, pp. 2376–2383.

H. Spies, Jähne, B., and Barron, J. L., “Regularised range flow”, in European Conference on Computer Vision (ECCV), 2000, vol. 2, p. 785--799.

J. Lellmann and Schnörr, C., “Regularizers for Vector-Valued Data and Labeling Problems in Image Processing”, Control Systems and Computers, vol. 2, pp. 43–54, 2011.

J. C. Rubio and Ommer, B., “Regularizing Max-Margin Exemplars by Reconstruction and Generative Models”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, p. 4213--4221.

Technical Report (2.8 MB)

A. Bhowmik, Gumhold, S., Rother, C., and Brachmann, E., “Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task”, in CVPR 2020 (oral), 2020.

PDF (2.74 MB)

A. Bhowmik, Gumhold, S., Rother, C., and Brachmann, E., “Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task”, 2019.

H. Reinecke, Fantana, N. L., Haußecker, H., and Jähne, B., “Rekonstruktion von Schreiberkurven”, in Mustererkennung 1997, 1997, p. 527--536.

N. von Schmude, Lothe, P., and Jähne, B., “Relative Pose Estimation from Straight Lines using Parallel Line Clustering and its Application to Monocular Visual Odometry”, in Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2016.

C. S. Garbe and Jähne, B., “Reliable estimates of the sea surface heat flux from image sequences”, in Proceedings of the 23th DAGM Symposium on Pattern Recognition, München, 2001, p. 194--201.

U. Köthe, “Reliable Low-Level Image Analysis”, Habilitation thesis. Department Informatik, University of Hamburg, Hamburg, 2008.

Technical Report (12.44 MB)

D. Withopf, “Reliable Real-Time Vehicle Detection and Tracking”. IWR, Fakultät für Mathematik und Informatik, Univ.\ Heidelberg, 2007.

H. Zhang, Hamprecht, F. A., and Amann, A., “Report about VOCs Dataset's Analysis based on Random Forests”, in Proceedings of the HPC-Asia05, 2005, pp. 603-607.

Technical Report (232.13 KB)

P. S. Liss, Watson, A. J., Bock, E. J., Jähne, B., Asher, W. E., Frew, N. M., Hasse, L., Korenowski, G. M., Merlivat, L., Phillips, L. F., Schlüssel, P., and Woolf, D. K., “Report Group 1 - Physical processes in the microlayer and the air-sea exchange of trace gases”, The Sea Surface and Global Change. Cambridge University Press, p. 1--33, 1997.

C. Schnörr, “Repräsentation von Bilddaten mit einem konvexen Variationsansatz”, in Mustererkennung 1996, Berlin, Heidelberg, 1996, pp. 21–28.

C. Schnörr, “Representation of Images by a Convex Variational Diffusion Approach”, FB Informatik, Universität Hamburg, FBI-HH-M-256/96, 1996.

B. Jähne, Jähne, B., and Haußecker, H., “Representation of multidimensional signals”, Computer Vision and Applications. A Guide for Students and Practitioners. Academic Press, p. 211--272, 2000.

B. Jähne, Haußecker, H., Platt, U., Schurr, U., and Stitt, M., “The research unit (Forschergruppe) Image Sequence Processing to Study Dynamical Processes”, in Proc.\ 3D Image Analysis and Synthesis'97, Erlangen (Germany), November 17--18, 1997, 1997, p. 107--114.

B. Saussen, “Retention Time Domain Registration of Liquid Chromatography/Mass Spectrometry Data”, University of Heidelberg, 2007.

D. Kotovenko, Wright, M., Heimbrecht, A., and Ommer, B., “Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.

M. Wenig, Kuhl, S., Beirle, S., Bucsela, E., Jähne, B., Platt, U., Gleason, J., and Wagner, T., “Retrieval and analysis of stratospheric NO$_2$ from the Global Ozone Monitoring Experiment”, J. Geophys. Res., vol. 109, p. D04315, 1--11, 2004.

C. Leue, Wenig, M., Platt, U., Jähne, B., Geißler, P., and Haußecker, H., “Retrieval of Atmospheric Trace Gas Concentrations”, Handbook of Computer Vision and Applications, vol. 3: Systems and Applications. Academic Press, pp. 783-805, 1999.

M. Heiler and Schnörr, C., “Reverse-Convex Programming for Sparse Image Codes”, in Proc. Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05), 2005, vol. 3757, pp. 600-616.

K. Roth, Milbich, T., Sinha, S., Gupta, P., Ommer, B., and Cohen, J. Paul, “Revisiting Training Strategies and Generalization Performance in Deep Metric Learning”, International Conference on Machine Learning (ICML). 2020.

J. M. Álvarez, Gevers, T., Diego, F., and López, A. M., “Road Geometry Classification by Adaptive Shape Models”, IEEE Transactions on Intelligent Transportation Systems (ITS), vol. 99, pp. 1-10, 2012.

D. Breitenreicher and Schnörr, C., “Robust 3D object registration without explicit correspondence using geometric integration”, Machine Vision and Applications, vol. 21, pp. 601-611, 2010.

Technical Report (1.65 MB)

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