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2021
P. Esser, Rombach, R., and Ommer, B., “Taming Transformers for High-Resolution Image Synthesis”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.
S. Lang and Ommer, B., “Transforming Information Into Knowledge: How Computational Methods Reshape Art History”, Digital Humanities Quaterly (DHQ), vol. 15, no. 3, 2021.
S. Lang and Ommer, B., “Transforming Information Into Knowledge: How Computational Methods Reshape Art History”, Digital Humanities Quaterly (DHQ), vol. 15, no. 3, 2021.
2020
S. Tourani, Shekhovtsov, A., Rother, C., and Savchynskyy, B., “Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization”, in AISTATS 2020, 2020.PDF icon PDF (2.58 MB)
2019
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.
S. Xiao, “Tracking Dividing Cells Using Spatio-Temporal Embeddings”, Heidelberg University, 2019.
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.
P. Esser, Haux, J., Milbich, T., and Ommer, B., “Towards Learning a Realistic Rendering of Human Behavior”, in European Conference on Computer Vision (ECCV - HBUGEN), 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.
2015
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.
J. H. Kappes, Petra, S., Schnörr, C., and Zisler, M., “TomoGC: Binary Tomography by Constrained Graph Cuts”, in Proc.~GCPR, 2015.PDF icon Technical Report (2.46 MB)
J. H. Kappes, Petra, S., Schnörr, C., and Zisler, M., “TomoGC: Binary Tomography by Constrained Graph Cuts”, in Proc. GCPR, 2015.
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.PDF icon Technical Report (2.39 MB)
D. Trofimova, “Towards Four Dimensional Visualization of Air-Water Gas Exchange”, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, 2015.
P. Bell and Ommer, B., “Training Argus”, Kunstchronik. Monatsschrift für Kunstwissenschaft, Museumswesen und Denkmalpflege, vol. 68, p. 414--420, 2015.
2014
J. - M. Gottfried, Nair, R., Meister, S., Garbe, C. S., and Kondermann, D., “Time of flight motion compensation revisited”, in International Conference on Image Processing, ICIP 2014, 2014.
J. Esparza, Helmle, M., and Jähne, B., “Towards surround stereo vision: analysis of a new surround view camera configuration for driving asistance applications”, in 17th International Conference on Intelligent Transportation Systems (ITSC 2014), 2014.
L. Fiaschi, Diego, F., Grosser, K. - H., Schiegg, M., Köthe, U., Zlatic, M., and Hamprecht, F. A., “Tracking indistinguishable translucent objects over time using weakly supervised structured learning”, in CVPR. Proceedings, 2014, pp. 2736 - 2743.PDF icon Technical Report (1.47 MB)
S. Lenor, Martini, J., Jähne, B., Stopper, U., Weber, S., and Ohr, F., “Tracking-based visibility estimation”, in Pattern Recognition, 36th German Conference, GCPR 2014, Münster, Germany, September 2-5, 2014, 2014, vol. 8753, p. 365--376.
2013
D. Lefloch, Nair, R., Lenzen, F., Schäfer, H., Streeter, L., and Cree, M. J., “Technical Foundation and Calibration Methods for Time-of-Flight Cameras”, in Time-of-Flight Imaging: Algorithms, Sensors and Applications, 2013, vol. 8200.
D. Lefloch, Nair, R., Lenzen, F., Schäfer, H., Streeter, L., Cree, M. J., Koch, R., and Kolb, A., “Technical Foundation and Calibration Methods for Time-of-Flight Cameras”, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, vol. 8200. Springer, pp. 3-24, 2013.
B. Goldlücke, Strekalovskiy, E., and Cremers, D., “Tight convex relaxations for vector-valued labeling”, SIAM Journal on Imaging Sciences, 2013.
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.
P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Towards a Computer-based Understanding of Medieval Images”, in Scientific Computing & Cultural Heritage, Springer, 2013, p. 89--97.
J. H. Kappes, Speth, M., Reinelt, G., and Schnörr, C., “Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization”, in CVPR, 2013.PDF icon Technical Report (623.84 KB)
J. H. Kappes, Speth, M., Reinelt, G., and Schnörr, C., “Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization”, in CVPR, 2013.
B. X. Kausler, “Tracking-by-Assignment as a Probabilistic Graphical Model with Applications in Developmental Biology”. University of Heidelberg, 2013.
2011
P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Top-down Analysis of Low-level Object Relatedness Leading to Semantic Understanding of Medieval Image Collections”, in Conference on Computer Vision and Image Analysis of Art II, 2011, vol. 7869, p. 61--69.PDF icon Technical Report (11.06 MB)
L. Maier-Hein, Franz, A. M., Fangerau, M., Schmidt, M., Seitel, A., Mersmann, S., Kilgus, T., Groch, A., Yung, K., Santos, T. R. dos, and Meinzer, H. - P., “Towards mobile augmented reality for on-patient visualization of medical images”, in Bildverarbeitung für die Medizin (2011), 2011, p. 389--393.
2010
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.
B. Glocker, T. Heibel, H., Navab, N., Kohli, P., and Rother, C., “TriangleFlow: Optical flow with triangulation-based higher-order likelihoods”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6313 LNCS, pp. 272–285.
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.
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.PDF icon 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.

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