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Publications

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2010
R. Nair, “Construction and analysis of random tree ensembles”, University of Heidelberg, 2010.
J. Lellmann and Schnörr, C., “Continuous Multiclass Labeling Approaches and Algorithms”, Univ. of Heidelberg, 2010.
S. Vicente, Kolmogorov, V., and Rother, C., “Cosegmentation revisited: Models and optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6312 LNCS, pp. 465–479.
2011
C. N. Straehle, Köthe, U., Knott, G. W., and Hamprecht, F. A., “Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images”, in MICCAI 2011, Proceedings., 2011, vol. 6891, pp. 653-660.PDF icon Technical Report (1.69 MB)
M. Erz, “Charakterisierung von Laufzeitkamerasystemen für Lumineszenzlebensdauermessungen”, vol. Dissertation. IWR, Fakultät für Physik und Astronomie, Univ. Heidelberg, 2011.
R. Rocholz, Wanner, S., Schimpf, U., and Jähne, B., “Combined visualization of wind waves and water surface temperature”, in Gas Transfer at Water Surfaces 2010, 2011, p. 496--506.
C. Kräuter, Richter, K. E., Jähne, B., Mesarchaki, E., and Williams, J., “A comparative lab study of tansfer velocities of volatile tracers with widely varying solubilities”, in DPG Frühjahrstagung Dresden, Fachverband Umweltphysik, 2011.
F. O. Kaster, Weber, M. - A., and Hamprecht, F. A., “Comparative Validation of Graphical Models for Learning Tumor Segmentations from Noisy Manual Annotations”, in LNCS, 2011, vol. LNCS 6533, pp. 74-85.PDF icon Technical Report (544.56 KB)
J. Lellmann and Schnörr, C., “Continuous Multiclass Labeling Approaches and Algorithms”, SIAM J.~Imag.~Sci., vol. 4, pp. 1049-1096, 2011.PDF icon Technical Report (4.31 MB)
J. Lellmann and Schnörr, C., “Continuous Multiclass Labeling Approaches and Algorithms”, CoRR, vol. abs/1102.5448, 2011.
J. Schlecht and Ommer, B., “Contour-based Object Detection”, in BMVC, 2011, p. 1--9.PDF icon Technical Report (2.62 MB)
2012
M. Geese, Jähne, B., and Ruhnau, P., “CNN Based Dark Signal Non-Uniformity Estimation”, CNNA, pp. 1-6, 2012.
M. Geese, Ruhnau, P., and Jähne, B., “CNN based dark signal non-uniformity estimation”, in Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on, 2012, p. 1--6.
S. Petra, Schnörr, C., and Schröder, A., “Critical Parameter Values and Reconstruction Properties of Discrete Tomography: Application to Experimental Fluid Dynamics”. 2012.
A. Shekhovtsov, Kohli, P., and Rother, C., “Curvature prior for MRF-based segmentation and shape inpainting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7476 LNCS, pp. 41–51.
A. Shekhovtsov, Kohli, P., and Rother, C., “Curvature prior for MRF-based segmentation and shape inpainting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7476 LNCS, pp. 41–51.
A. Shekhovtsov, Kohli, P., and Rother, C., “Curvature prior for MRF-based segmentation and shape inpainting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7476 LNCS, pp. 41–51.
2013
S. Mersmann, Seitel, A., Erz, M., Jähne, B., Nickel, F., Mieth, M., Mehrabi, A., and Maier-Hein, L., “Calibration of time-of-flight cameras for accurate intraoperative surface reconstruction”, Med. Phys., vol. 40, p. 082701, 2013.
F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “A Class of Quasi-Variational Inequalities for Adaptive Image Denoising and Decomposition”, Computational Optimization and Applications (COAP), vol. 54 (2), pp. 371-398, 2013.
F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “A class of quasi-variational inequalities for adaptive image denoising and decomposition”, Computational Optimization and Applications, vol. 54, pp. 371-398, 2013.PDF icon Technical Report (748.66 KB)
D. Breitenreicher, Lellmann, J., and Schnörr, C., “COAL: a generic modelling and prototyping framework for convex optimization problems of variational image analysis”, Optimization Methods and Software, vol. 28, pp. 1081-1094, 2013.PDF icon Technical Report (1.69 MB)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Sungwoong, K., Kausler, B. X., Lellmann, J., Komodakis, N., and Rother, C., “A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems”, in CVPR 2013. Proceedings, 2013.PDF icon Technical Report (1.35 MB)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Lellmann, J., Komodakis, N., and Rother, C., “A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem”, in CVPR, 2013.PDF icon Technical Report (1.35 MB)
M. Schiegg, Hanslovsky, P., Kausler, B. X., Hufnagel, L., and Hamprecht, F. A., “Conservation Tracking”, in ICCV 2013. Proceedings, 2013, p. 2928--2935.PDF icon Technical Report (5.22 MB)
B. Schmitzer and Schnörr, C., “Contour Manifolds and Optimal Transport”. 2013.
P. Swoboda and Schnörr, C., “Convex Variational Image Restoration with Histogram Priors”, SIAM J.~Imag.~Sci., vol. 6, pp. 1719-1735, 2013.PDF icon Technical Report (553.54 KB)
B. Maco, Holtmaat, A., Cantoni, M., Kreshuk, A., Straehle, C. N., Hamprecht, F. A., and Knott, G. W., “Correlative in vivo 2 photon and focused ion beam scanning electron microscopy of cortical neurons”, PloS one, vol. 8 (2), 2013.PDF icon Technical Report (2.13 MB)
S. Meister, “On Creating Reference Data for Performance Analysis in Image Processing”. University of Heidelberg, 2013.
S. Petra, Schnörr, C., and Schröder, A., “Critical Parameter Values and Reconstruction Propertiesof Discrete Tomography: Application to Experimental FluidDynamics”, Fundamenta Informaticae, vol. 125, p. 285--312, 2013.PDF icon Technical Report (1.42 MB)
2014
L. Maier-Hein, Mersmann, S., Kondermann, D., Bodenstedt, S., Sanchez, A., Stock, C., Kenngott, H., Eisenmann, M., and Speidel, S., “Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images”, in MICCAI, 2014.
J. Welbl, “Casting Random Forests as Artificial Neural Networks (and Profiting from It)”, in GCPR. Proceedings, 2014, pp. 765-771.PDF icon Technical Report (376.24 KB)
C. Zhang, Yarkony, J., and Hamprecht, F. A., “Cell detection and segmentation using correlation clustering”, in MICCAI. Proceedings, 2014, pp. 9-16.PDF icon Technical Report (8.06 MB)
L. Nagel, Krall, K. Ellen, and Jähne, B., “Comparative heat and gas exchange measurements in the Heidelberg Aeolotron, a large annular wind-wave tank”, Ocean Sci. Discuss., vol. 11, p. 1691--1718, 2014.
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, 2014.
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.PDF icon Technical Report (3.32 MB)

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