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Publications

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2021
D. Gonzalez-Alvarado, Zeilmann, A., and Schnörr, C., “Assignment Flows and Nonlocal PDEs on Graphs”, GCPR, in press. 2021.
2020
A. Zern, Zeilmann, A., and Schnörr, C., “Assignment Flows for Data Labeling on Graphs: Convergence and Stability”, preprint: arXiv, 2020.
A. Zern, Zeilmann, A., and Schnörr, C., “Assignment Flows for Data Labeling on Graphs: Convergence and Stability”, preprint: arXiv, 2020.
A. Zeilmann, Savarino, F., Petra, S., and Schnörr, C., “Geometric Numerical Integration of the Assignment Flow”, Inverse Problems, vol. 36, p. 034004 (33pp), 2020.
A. Zern, Zisler, M., Petra, S., and Schnörr, C., “Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment”, Journal of Mathematical Imaging and Vision, 2020.
A. Zern, Zisler, M., Petra, S., and Schnörr, C., “Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment”, Journal of Mathematical Imaging and Vision, 2020.
2019
L. Cerrone, Zeilmann, A., and Hamprecht, F. A., “End-to-End Learned Random Walker for Seeded Image Segmentation”, CVPR. Proceedings. pp. 12559-12568, 2019.
A. Zeilmann, Savarino, F., Petra, S., and Schnörr, C., “Geometric Numerical Integration of the Assignment Flow”, Inverse Problems, 2019.
S. Berg, 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., “ilastik: interactive machine learning for (bio)image analysis”, Nature Methods, vol. 16, pp. 1226-1232, 2019.
M. Zisler, Zern, A., Petra, S., and Schnörr, C., “Self-Assignment Flows for Unsupervised Data Labeling on Graphs”, preprint: arXiv, 2019.
M. Zisler, Zern, A., Petra, S., and Schnörr, C., “Self-Assignment Flows for Unsupervised Data Labeling on Graphs”, preprint: arXiv, 2019.
A. Zern, Zisler, M., Petra, S., and Schnörr, C., “Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment”, preprint: arXiv, 2019.
A. Zern, Zisler, M., Petra, S., and Schnörr, C., “Unsupervised Assignment Flow: Label Learning on Feature Manifolds by Spatially Regularized Geometric Assignment”, preprint: arXiv, 2019.
M. Zisler, Zern, A., Petra, S., and Schnörr, C., “Unsupervised Labeling by Geometric and Spatially Regularized Self-Assignment”, in Proc. SSVM, 2019.
M. Zisler, Zern, A., Petra, S., and Schnörr, C., “Unsupervised Labeling by Geometric and Spatially Regularized Self-Assignment”, in Proc. SSVM, 2019.
2018
T. Hodaň, Michel, F., Brachmann, E., Kehl, W., Buch, A. Glent, Kraft, D., Drost, B., Vidal, J., Ihrke, S., Zabulis, X., Sahin, C., Manhardt, F., Tombari, F., Kim, T. Kyun, Matas, J., and Rother, C., “BOP: Benchmark for 6D object pose estimation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, vol. 11214 LNCS, pp. 19–35.
A. Arnab, Zheng, S., Jayasumana, S., Romera-paredes, B., Kirillov, A., Savchynskyy, B., Rother, C., Kahl, F., and Torr, P., “Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation”, Cvpr, vol. XX, pp. 1–15, 2018.
A. Zern, Rohr, K., and Schnörr, C., “Geometric Image Labeling with Global Convex Labeling Constraints”, in EMMCVPR, 2018, vol. 10746, pp. 533–547.
A. Zeilmann, Savarino, F., Petra, S., and Schnörr, C., “Geometric Numerical Integration of the Assignment Flow”, preprint: arXiv, 2018.
A. Zern, Zisler, M., Aström, F., Petra, S., and Schnörr, C., “Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment”, GCPR. Proceedings. pp. 698-713, 2018.PDF icon Technical Report (5.23 MB)
A. Zern, Zisler, M., Aström, F., Petra, S., and Schnörr, C., “Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment”, GCPR. Proceedings. pp. 698-713, 2018.PDF icon Technical Report (5.23 MB)
A. Zern, Zisler, M., Aström, F., Petra, S., and Schnörr, C., “Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment”, in GCPR, 2018.
A. Zern, Zisler, M., Aström, F., Petra, S., and Schnörr, C., “Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment”, in GCPR, 2018.
2017
A. Zern, Rohr, K., and Schnörr, C., “Geometric Image Labeling with Global Convex Labeling Constraints”, in Proc. EMMCVPR, 2017.
M. Zisler, Savarino, F., Petra, S., and Schnörr, C., “Gradient Flows on a Riemannian Submanifold for Discrete Tomography”, in Proc. GCPR, 2017.
M. Zisler, Aström, F., Petra, S., and Schnörr, C., “Image Reconstruction by Multilabel Propagation”, in Proc. SSVM, 2017, vol. 10302.
A. Kirillov, Schlesinger, D., Zheng, S., Savchynskyy, B., Torr, P. H. S., and Rother, C., “Joint training of generic CNN-CRF models with stochastic optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10112 LNCS, pp. 221–236.
P. Markowsky, Reith, S., Zuber, T. E., König, R., Rohr, K., and Schnörr, C., “Segmentation of cell structure using model-based set covering with iterative reweighting”, in Proc. ISBI, 2017.
2016
M. Zisler, Petra, S., Schnörr, C., and Schnörr, C., “Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints”, in Proc. GCPR, 2016.
M. Zisler, Kappes, J. H., Schnörr, C., Petra, S., and Schnörr, C., “Non-Binary Discrete Tomography by Continuous Non-Convex Optimization”, IEEE Comp. Imaging, vol. 2, pp. 335-347, 2016.
2015
D. Kiefhaber, Zappa, C. J., and Jähne, B., “Influence of natural surfactants on short wind waves in the coastal Peruvian waters”, vol. 12, pp. 1291–1325, 2015.
J. Funke, Hamprecht, F. A., and Zhang, C., “Learning to Segment: Training Hierarchical Segmentation under a Topological Loss”, in MICCAI. Proceedings, Part III, 2015, vol. 9351, pp. 268-275.PDF icon Technical Report (2.92 MB)
S. Zheng, Prisacariu, V. Adrian, Averkiou, M., Cheng, M. Ming, Mitra, N. J., Shotton, J., Torr, P. H. S., and Rother, C., “Object proposals estimation in depth image using compact 3D shape manifolds”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9358, pp. 196–208.
N. J. Mitra, Stam, J., Xu, K., Cheng, M. - M., Prisacariu, V. Adrian, Zheng, S., Torr, P. H. S., and Rother, C., “Pacific Graphics 2015 DenseCut: Densely Connected CRFs for Realtime GrabCut”, vol. 34, 2015.
J. Mund, Zouhar, A., Meyer, L., Fricke, H., and Rother, C., “Performance evaluation of LiDAR point clouds towards automated FOD detection on airport aprons”, in Proceedings of ATACCS 2015 - 5th International Conference on Application and Theory of Automation in Command and Control Systems, 2015, pp. 85–94.

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