Publications

F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., “Variational Adaptive Correlation Method for Flow Estimation”, IEEE Transactions on Image Processing, vol. 21, pp. 3053 – 3065, 2012.

F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., “Variational Adaptive Correlation Method for Flow Estimation”, IEEE Transactions on Image Processing, vol. 21, p. 3053 -- 3065, 2012.

Technical Report (18.81 MB)

F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., “Variational Adaptive Correlation Method for Flow Estimation”, IEEE Transactions on Image Processing, vol. 21, 6, pp. 3053 - 3065, 2011.

B. Michael Kelm, Kaster, F. O., Henning, A., Weber, M. - A., Bachert, P., Bösinger, P., Hamprecht, F. A., and Menze, B. H., “Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images”, NMR in Biomedicine, vol. 25(1), pp. 1-13, 2011.

Technical Report (1.94 MB)

P. Kohli, Nickisch, H., Rother, C., and Rhemann, C., “User-centric learning and evaluation of interactive segmentation systems”, International Journal of Computer Vision, vol. 100, pp. 261–274, 2012.

T. Milbich, Ghori, O., and Ommer, B., “Unsupervised Representation Learning by Discovering Reliable Image Relations”, Pattern Recognition, vol. 102, 2020.

B. Brattoli, Büchler, U., Dorkenwald, M., Reiser, P., Filli, L., Helmchen, F., Wahl, A. - S., and Ommer, B., “Unsupervised behaviour analysis and magnification (uBAM) using deep learning”, Nature Machine Intelligence, 2021.

A. Zern, Zisler, M., Petra, S., and Schnörr, C., “Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment”, Journal of Mathematical Imaging and Vision, 2020.

A. Zern, Zisler, M., Petra, S., and Schnörr, C., “Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment”, preprint: arXiv, 2019.

C. Schnörr, “Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals”, vol. 4, pp. 189–198, 1994.

A. Lifermann, Jähne, B., and Ramamonjiarisoa, A., “Une ètude en soufflerie de la rèflexion des hyperfrèquences par des champs de houles et de vagues”, Oceanologia Acta, vol. SP, p. 15--22, 1987.

B. Jähne and Riemer, K., “Two-dimensional wave number spectra of small-scale water surface waves”, J. Geophys. Res., vol. 95, p. 11531--11646, 1990.

S. Lang and Ommer, B., “Transforming Information Into Knowledge: How Computational Methods Reshape Art History”, Digital Humanities Quaterly (DHQ), vol. 15, no. 3, 2021.

P. Bell and Ommer, B., “Training Argus”, Kunstchronik. Monatsschrift für Kunstwissenschaft, Museumswesen und Denkmalpflege, vol. 68, p. 414--420, 2015.

M. Hanselmann, Köthe, U., Kirchner, M., Renard, B. Y., Amstalden, E. R., Glunde, K., Heeren, R. M. A., and Hamprecht, F. A., “Towards Digital Staining using Imaging Mass Spectrometry and Random Forests”, Journal of Proteome Research, vol. 8, pp. 3558-3567, 2009.

Technical Report (1.47 MB)

J. P. Kauppi, Kandemir, M., Saarinen, V. M., Hirvenkari, L., Parkkonen, L., Klami, A., Hari, R., and Kaski, S., “Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals”, NeuroImage, vol. 112, pp. 288-298, 2015.

Technical Report (2.39 MB)

M. Esposito, Hennersperger, C., Göbl, R., Demaret, L., Storath, M., Navab, N., Baust, M., and Weinmann, A., “Total variation regularization of pose signals with an application to 3D freehand ultrasound”, IEEE Transactions on Medical Imaging, vol. 38(10), pp. 2245-2258, 2019.

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. Meine, Köthe, U., and Stelldinger, P., “A Topological Sampling Theorem for Robust Boundary Reconstruction and Image Segmentation”, Discrete Applied Mathematics, vol. 157, pp. 524-541, 2008.

S. Petra and Schnörr, C., “TomoPIV meets Compressed Sensing”, Pure Math. Appl., vol. 20, pp. 49 – 76, 2009.

S. Petra and Schnörr, C., “TomoPIV meets Compressed Sensing”, Pure Math.~Appl., vol. 20, p. 49 -- 76, 2009.

Technical Report (409.1 KB)

J. Davis, Jähne, B., Kolb, A., Raskar, R., Theobalt, C., Davis, J., Jähne, B., Raskar, R., Theobalt, C., and Kolb, A., Eds., “Time-of-Flight Imaging: Algorithms, Sensors and Applications (Dagstuhl Seminar 12431)”, Dagstuhl Reports, vol. 2, p. 79--104, 2013.

B. Goldlücke, Strekalovskiy, E., and Cremers, D., “Tight convex relaxations for vector-valued labeling”, SIAM Journal on Imaging Sciences, 2013.

A. Berthe, Kondermann, D., Christensen, C., Goubergrits, L., Garbe, C. S., Affeld, K., and Kertzscher, U., “Three-dimensional, three-component wall-PIV”, Exp. Fluids, vol. 48, p. online, 2010.

H. Kubinyi, Hamprecht, F. A., and Mietzner, T., “Threedimensional Quantitative Similarity-Activity Relationships (3DQSiAR) from SEAL Similarity Matrices”, Journal of Medicinal Chemistry, vol. 41, pp. 2553-2564, 1998.

J. Schmähling, Hamprecht, F. A., and Hoffmann, D. M. P., “A three-dimensional measure of surface roughness based on mathematical morphology”, International Journal of Machine Tools and Manufacture, vol. 46 (14), pp. 1764-1769, 2006.

Technical Report (524.97 KB)

C. Cali, Baghabra, J., Boges, D. J., Holst, G. R., Kreshuk, A., Hamprecht, F. A., Srinivasan, M., Lehväslaiho, H., and Magistretti, P. J., “Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues”, Journal of Comparative Neurology, vol. 524, pp. 23-38, 2015.

M. Bühl and Hamprecht, F. A., “Theoretical Investigation of NMR Chemical Shifts and Reactivities of Oxovanadium (V) Compounds”, Journal of Computational Chemistry, vol. 19, pp. 113-122, 1998.

J. Weickert and Schnörr, C., “A Theoretical Framework for Convex Regularizers in PDE–Based Computation of Image Motion”, Int. J. Computer Vision, vol. 45, pp. 245–264, 2001.

H. Rapp, Frank, M., Hamprecht, F. A., and Jähne, B., “A Theoretical and Experimental Investigation of the Systematic Errors and Statistical Uncertainties of Time-of-Flight Cameras”, Int. J. Intelligent Systems Technologies and Applications, vol. 5, pp. 402-413, 2008.

Technical Report (798.23 KB)

H. Rapp, Frank, M., Hamprecht, F. A., and Jähne, B., “A theoretical and experimental investigation of the systematic errors and statistical uncertainties of time-of-flight cameras”, Int. J. Intelligent Systems Technologies and Applications, vol. 5, p. 402--413, 2008.

M. Frank, Plaue, M., Rapp, H., Köthe, U., Jähne, B., and Hamprecht, F. A., “Theoretical and Experimental Error Analysis of Continuous-Wave Time-Of-Flight Range Cameras”, Optical Engineering, vol. 48, 013602, 2009.

Technical Report (2.03 MB)

M. Frank, Plaue, M., Rapp, H., Köthe, U., Jähne, B., and Hamprecht, F. A., “Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras”, Opt. Eng., vol. 48, p. 013602, 2009.

J. Shotton, Winn, J., Rother, C., and Criminisi, A., “TextonBoost for image understanding: Multi-class object recognition and segmentation by jointly modeling texture, layout, and context”, International Journal of Computer Vision, vol. 81, pp. 2–23, 2009.

Pages