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J. Shotton, Winn, J., Rother, C., and Criminisi, A., “TextonBoost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2006, vol. 3951 LNCS, pp. 1–15.

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.

H. Haußecker, Spies, H., and Jähne, B., “Tensor-based image sequence processing techniques for the study of dynamical processes”, in Proc. Intern. Symp. On Real-time Imaging and Dynamic Analysis, 1998, p. 704--711.

H. Haußecker and Jähne, B., “A tensor approach for precise computation of dense displacement vector fields”, in Proceedings of the 19th DAGM Symposium on Pattern Recognition, Braunschweig, 1997, p. 199--208.

H. Haußecker and Jähne, B., “A tensor approach for local structure analysis in multi-dimensional images”, in 3D Image Analysis and Synthesis, 1996, p. 171--178.

B. H. Menze, Ur, J. A., and Sherratt, A. G., “Tell Spotting - Surveying Near Eastern Settlement Mounds from Space”, in Proceedings of the XXth CIPA International Symposium 2005, Torino, Italy, 2005, pp. 217-223.

Technical Report (2.53 MB)

B. Jähne, Massen, R., Nickolay, B., and Scharfenberg, H., Technische Bildverarbeitung - Maschinelles Sehen. Springer, 1995.

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.

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 (2.58 MB)

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.

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W. Mischler, “Systematic Measurements of Bubble Induced Gas Exchange for Trace Gases with Low Solubilities”, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2014.

S. Hader, “System Concept for Image Sequence Classification in Laser Welding”, Pattern Recognition, vol. 2781. Springer, pp. 212-219, 2003.

M. Großkinsky, “Synaptic Cleft Prediction on Electron Microsope Images”, Heidelberg University, 2019.

F. Silvestri, Reinelt, G., and Schnörr, C., “Symmetry-free SDP Relaxations for Affine Subspace Clustering”. 2016.

J. Neumann, Schnörr, C., and Steidl, G., “SVM-based Feature Selection by Direct Objective Minimisation”, in Pattern Recognition, Proc. 26th DAGM Symposium, 2004, vol. 3175, pp. 212-219.

R. Nair, Ruhl, K., Lenzen, F., Meister, S., Schäfer, H., Garbe, C. S., Eisemann, M., Magnor, M., and Kondermann, D., “A Survey on Time-of-Flight Stereo Fusion”, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, vol. 8200. Springer, pp. 105-127, 2013.

R. Nair, Ruhl, K., Lenzen, F., Meister, S., Schäfer, H., Garbe, C. S., Eisemann, M., Magnor, M., and Kondermann, D., “A Survey on Time-of-Flight Stereo Fusion”, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, vol. 8200. Springer, pp. 105-127, 2013.

Technical Report (6.05 MB)

R. Nair, Ruhl, K., Lenzen, F., Meister, S., Schäfer, H., Garbe, C. S., Eisemann, M., and Kondermann, D., “A Survey on Time-of-Flight Stereo Fusion”, in Time-of-Flight Imaging: Algorithms, Sensors and Applications, 2013, vol. 8022, pp. 105-127.

T. Hara, Uz, B. M., Wei, H., Edson, J. B., Frew, N. M., McGilles, W. R., McKenna, S. P., Bock, E. J., Haußecker, H., and Schimpf, U., “Surface wave observations during CoOP experiments and their relations to air-sea gas transfer”, in Gas Transfer at Water Surfaces, 2002, vol. 127, p. 45--49.

M. Gutsche, “Surface Velocity Measurements at the Aeolotron by Means of Active Thermography”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2014.

M. Gutsche, “Surface Velocity Measurements at the Aeolotron by Means of Active Thermography”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2014.

M. Bleyer, Rother, C., and Kohli, P., “Surface stereo with soft segmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 1570–1577.

C. S. Garbe, Schimpf, U., and Jähne, B., “A surface renewal model to analyze infrared image sequences of the ocean surface for the study of air-sea heat and gas exchange”, J. Geophys. Res., vol. 109, pp. 1-18, 2004.

C. S. Garbe, Schimpf, U., and Jähne, B., “A surface renewal model to analyze infrared image sequences for the study of air-sea heat and gas exchange”, in Geophysical Research Abstracts, 2003, p. 11893.

C. Wolf, “Surface Properties of Breaking Water Waves”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1994.

H. Spies, Jähne, B., and Barron, J. L., “Surface expansion from range data sequences”, in Proceedings of the 23th DAGM Symposium on Pattern Recognition, 2001, p. 163--169.

D. Singaraju, Rother, C., and Rhemann, C., “Supplementary material for New Appearance Models for Image Matting”, 2009.

S. Nowozin and Sharp, T., “Supplementary Material : Decision Tree Fields”, Iccv, 2011.

“A Supplementary Material CEREALS-Cost-Effective REgion-based Active Learning for Semantic Segmentation”, 2018.

B. Goldlücke, Aubry, M., Kolev, K., and Cremers, D., “A super-resolution framework for high-accuracy multiview reconstruction”, Int. J. Comp. Vision, vol. 106, p. 172--191, 2014.

Y. Censor, Petra, S., and Schnörr, C., “Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case”, preprint: arXiv, 2019.

Y. Censor, Petra, S., and Schnörr, C., “Superiorization vs. Accelerated Convex Optimization: The Superiorized/Regularized Least Squares Case”, J. Appl. Numer. Optimization (in press; arXiv:1911.05498), vol. 2, pp. 15-62, 2020.

M. Desana and Schnörr, C., “Sum-Product Graphical Models”, Machine Learning, 2019.

M. Desana and Schnörr, C., “Sum-Product Graphical Models”, Machine Learning, vol. 109, pp. 135–173, 2020.

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