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Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2019). Geometric Numerical Integration of the Assignment Flow. Inverse Problems. https://doi.org/10.1088/1361-6420/ab2772

Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2018). Geometric Numerical Integration of the Assignment Flow. preprint: arXiv. https://arxiv.org/abs/1810.06970

Savchynskyy, B and Schmidt, S (2012). Getting Feasible Variable Estimates From Infeasible Ones: MRF Local Polytope Study. arXiv:1210.4081

Woodford, O J (2009). A Global Perspective on MAP Inference for Low-Level Vision Supplementary material to ICCV submission \# 1536. Optimization

Wanner, S, Straehle, C N and Goldlücke, B (2013). Globally Consistent Multi-Label Assignment on the Ray Space of 4D Light Fields. CVPR 2013. Proceedings. 1011-1018

Schmitzer, B and Schnörr, C (2015). Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes. J. Math. Imag. Vision. 52 436–458. http://link.springer.com/article/10.1007/s10851-014-0546-8

Schmitzer, B and Schnörr, C (2015). Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes. J.~Math.~Imag.~Vision. 52 436--458. http://link.springer.com/article/10.1007/s10851-014-0546-8

Technical Report (1.97 MB)

Kostrykin, L, Schnörr, C and Rohr, K (2019). Globally Optimal Segmentation of Cell Nuclei in Fluoroscence Microscopy Images using Shape and Intensity Information. Medical Image Analysis. https://doi.org/10.1016/j.media.2019.101536

Heers, J, Schnörr, C and Stiehl, H S (2001). Globally–Convergent Iterative Numerical Schemes for Non–Linear Variational Image Smoothing and Segmentation on a Multi–Processor Machine. IEEE Trans. Image Proc. 10 852–864

Leue, C, Wenig, M, Jähne, B and Platt, U (1998). GOME mißt atmosphärische Stickoxide. Globale Biomassenverbrennung und Industrieemissionen. Physik in unserer Zeit. 29 179

Schiegg, M, Hanslovsky, P, Haubold, C, Köthe, U, Hufnagel, L and Hamprecht, F A (2015). Graphical Model for Joint Segmentation and Tracking of Multiple Dividing Cell. Bioinformatics. 31 948-956. http://bioinformatics.oxfordjournals.org/content/early/2014/11/17/bioinformatics.btu764.full.pdf?keytype=ref&ijkey=mTXWsiFrci7R8tc

Technical Report (534.29 KB)

Ardizzone, L, Lüth, C, Kruse, J, Rother, C and Köthe, U (2019). Guided Image Generation with Conditional Invertible Neural Networks. http://arxiv.org/abs/1907.02392

Ardizzone, L, Lüth, C, Kruse, J, Rother, C and Köthe, U (2019). Guided Image Generation with Conditional Invertible Neural Networks. http://arxiv.org/abs/1907.02392

Jähne, (1999). Gut beleuchtet ist halb gemessen. QZ. 44 1283--1288. https://www.qz-online.de/qz-zeitschrift/archiv/artikel/art-der-lichtquelle-und-der-einstrahlbedingungen-sind-entscheidend-gut-beleuchtet-ist-halb-gemessen-345974.html

Jähne, B, Wais, T, Memery, L, Caulliez, G, Merlivat, L, Münnich, K O and Coantic, M (1985). He and Rn gas exchange experiments in the large wind-wave facility of IMST. J. Geophys. Res. 90 11,989--11,998

Lindner, R, Lou, X, Reinstein, J, Shoeman, R L, Hamprecht, F A and Winkler, A (2014). Hexicon 2: Automated Processing of Hydrogen-Deuterium Exchange Mass Spectrometry Data with Improved Deuteration Distribution Estimation. Journal of The American Society for Mass Spectrometry. 25 1018-1028

Technical Report (2.1 MB)

Bruhn, A, Jakob, T, Fischer, M, Weickert, J, Brüning, U and Schnörr, C (2004). High performance cluster computing with 3-D nonlinear diffusion filters. Real-Time Imaging. 10 41–51

Nair, R and Kondermann, D (2011). High Precision TOF-guided Depth from Stereo for Room Scanning. CVMP, Proceedings

Kräuter, C, Trofimova, D, Kiefhaber, D, Krah, N and Jähne, B (2014). High resolution 2-D fluorescence imaging of the mass boundary layer thickness at free water surfaces. J. Europ. Opt. Soc. Rap. Public. 9 14016

Kappes, J, Speth, M, Reinelt, G and Schnörr, C (2016). Higher-order Segmentation via Multicuts. Comp. Vision Image Understanding. 143 104–119

Kiefhaber, D, Reith, S, Rocholz, R and Jähne, B (2014). High-speed imaging of short wind waves by shape from refraction. J. Europ. Opt. Soc. Rap. Public. 9 14015

Donath, A and Kondermann, D (2013). How Good is Crowdsourcing for Optical Flow Ground Truth Generation?. submitted to CVPR

Andres, B, Köthe, U, Kröger, T and Hamprecht, F A (2010). How to Extract the Geometry and Topology from Very Large 3D Segmentations. ArXiv e-prints. http://arxiv.org/abs/1009.6215

Technical Report (1.44 MB)

Berg, S, Kutra, D, Kroeger, T, Straehle, C N, Kausler, B X, Haubold, C, Schiegg, M, Ales, J, Beier, T, Rudy, M, Eren, K, Cervantes, J I, Xu, B, Beuttenmüller, F, Wolny, A, Zhang, C, Köthe, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232

Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM Journal on Imaging Sciences. 11 1317-1362

Technical Report (2.62 MB)

Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM J. Imaging Science. 11 1317–1362. https://epubs.siam.org/doi/abs/10.1137/17M1150669

Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2017). Image Labeling by Assignment. J. Math. Imag. Vision. 58 211–238. Papers/Astroem2017.pdf

Frank, M and Hamprecht, F A (2011). Image-Based Supervision of a Periodically Working Machine. Pattern Analysis and Applications. 1-10

Technical Report (466.61 KB)

Jähne, B, Klinke, J and Waas, S (1994). Imaging of short ocean wind waves: a critical theoretical review. J. Opt. Soc. Am. A. 11 2197--2209

Meijering, E, Carpenter, A E, Peng, H, Hamprecht, F A and Olivo-Marin, J (2016). Imagining the future of bioimage analysis. Nature Biotechnology. 34 1250-1255

Technical Report (924.57 KB)

Censor, Y, Gibali, A, Lenzen, F and Schnörr, C (2016). The Implicit Convex Feasibility Problem and Its Application to Adaptive Image Denoising. J. Comp. Math. 34 608-623

Biller, A, Badde, S, Nagel, A, Neumann, J O, Wick, W, Hertenstein, A, Bendszus, M, Sahm, F, Benkhedah, N and Kleesiek, J (2016). Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression. American Journal of Neuroradiology. 37 66-73

Sanakoyeu, A, Ma, P, Tschernezki, V and Ommer, B (2021). Improving Deep Metric Learning by Divide and Conquer. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). https://arxiv.org/abs/2109.04003

Kiefhaber, D, Zappa, C J and Jähne, B (2015). Influence of natural surfactants on short wind waves in the coastal Peruvian waters. 12 1291–1325

Suhr, H, Wehnert, G, Schneider, K, Bittner, C, Scholz, T, Geißler, P, Jähne, B and Scheper, T (1995). In-situ microscopy for on-line characterization of cell-populations in bioreactors, including concentration measurements by depth from focus. Biotechnology and Bioengineering. 47 106--116

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