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2013
D. Kiefhaber, Rocholz, R., Bauer, P. Salomon, and Jähne, B., “Optical measurement of surface ocean waves”, in 3rd EOS Topical Meeting on Blue Photonics --- Optics in the Sea, 2013.
M. Geese, Ruhnau, P., and Jähne, B., “PRNU and DSNU Maximum Likelihood Estimation Using Sensor Statistics”, tm --- Technisches Messen, vol. 80, p. 321--328, 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.PDF icon Technical Report (6.05 MB)
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., 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.
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.
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.
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.
2012
M. Hanselmann, Röder, J., Köthe, U., Renard, B. Y., Heeren, R. M. A., and Hamprecht, F. A., “Active Learning for Convenient Annotation and Classification of Secondary Ion Mass Spectrometry Images”, Analytical Chemistry, vol. 85 (1), pp. 147-155, 2012.PDF icon Technical Report (2.58 MB)
M. Hanselmann, Röder, J., Köthe, U., Renard, B. Y., Heeren, R. M. A., and Hamprecht, F. A., “Active Learning for Convenient Annotation and Classification of Secondary Ion Mass Spectrometry Images”, Analytical Chemistry, vol. 85 (1), pp. 147-155, 2012.PDF icon Technical Report (2.58 MB)
J. Röder, Kunzmann, K., Nadler, B., and Hamprecht, F. A., “Active Learning with Distributional Estimates”, UAI 2012. Proceedings, pp. 715-725, 2012.PDF icon Technical Report (267.67 KB)
L. Nagel, Richter, K. E., and Jähne, B., “Active Thermography as a Link between Laboratory and Field Studies”, in SOLAS Open Science Conference, Washington State, USA, 2012.
V. Lempitsky, Blake, A., and Rother, C., “Branch-and-mincut: Global optimization for image segmentation with high-level priors”, Journal of Mathematical Imaging and Vision, vol. 44, pp. 315–329, 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.
M. Geese, Jähne, B., and Ruhnau, P., “CNN Based Dark Signal Non-Uniformity Estimation”, CNNA, pp. 1-6, 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.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
B. Jähne, “Gas transfer at water surfaces”, Environmental Fluid Mechanics - Memorial Volume in honour of Professor Gerhard H. Jirka. CRC Press/Balkema, p. 389--404, 2012.
R. Rocholz, Fahle, P., and Jähne, B., “High speed and high resolution wave imaging to investigate the initial generation of wind waves at very small fetch”. 2012.
J. Jancsary, Nowozin, S., and Rother, C., “Loss-specific training of non-parametric image restoration models: A new state of the art”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7578 LNCS, pp. 112–125.
J. Jancsary, Nowozin, S., and Rother, C., “Loss-specific training of non-parametric image restoration models: A new state of the art”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7578 LNCS, pp. 112–125.
J. Jancsary, Nowozin, S., and Rother, C., “Non-parametric crfs for image labeling”, in NIPS Workshop Modern Nonparametric Methods in Machine Learning, 2012, pp. 1–5.
B. Y. Renard, Xu, B., Kirchner, M., Zickmann, F., Winter, D., Korten, S., Brattig, N., Tzur, A., Hamprecht, F. A., and Steen, H., “Overcoming species boundaries in peptide identification with BICEPS”, Molecular and Cellular Proteomics, vol. 11, 2012.PDF icon Technical Report (444.6 KB)
C. Kräuter, Richter, K. E., Mesarchaki, E., Rocholz, R., Williams, J., and Jähne, B., “Partitioning of the Trasfer Resistance between Air and Water”, in SOLAS Open Science Conference, Washington State, USA, 2012.
C. Kräuter, Richter, K. E., Mesarchaki, E., Rocholz, R., Williams, J., and Jähne, B., “Partitioning of the Trasfer Resistance between Air and Water”, in SOLAS Open Science Conference, Washington State, USA, 2012.
D. Kondermann, Abraham, S., Förstner, W., Gehrig, S., Imiya, A., Jähne, B., Klose, F., Magor, M., Mayer, H., Mester, R., Pajdla, T., Reulke, R., and Zimmer, H., “On Performance Analysis of Optical Flow Algorithms”, in Outdoor and Large-Scale Real-Worls Scene Analysis, Dagstuhl-Workshop 2011, 2012, vol. LNCS, pp. 329-355.
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.
M. Geese, Ruhnau, P., and Jähne, B., “Scene based maximum likelihood PRNU and DSNU non uniformity correction”, in Forum Bildverarbeitung, 2012, p. 71--82.

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