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C. S. Garbe, Flatow, F., Klinger, M., Schepanski, K., Tegen, I., and Rannacher, R., “Transport of dust across the Sahara from satellite image sequence analysis”, in Eos Transactions, 2009, vol. 90, no. 52, p. EP21A-0565.

C. S. Garbe, Flatow, F., Klinger, M., Schepanski, K., Tegen, I., and Rannacher, R., “Transport of Sahara dust into the Atlantic Ocean from satellite image sequence analysis”, in SOLAS Open Science Conference, 2009, p. 27.

B. Glocker, T. Heibel, H., Navab, N., Kohli, P., and Rother, C., “TriangleFlow: Optical flow with triangulation-based higher-order likelihoods”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6313 LNCS, pp. 272–285.

B. Jähne, “Trockene Deposition von Gasen über Wasser (Gasaustausch)”, Austausch von Luftverunreinigungen an der Grenzfläche Atmospäre/Erdoberfläche, Zwischenbericht für das Umweltbundesamt zum Teilprojekt 1: Deposition von Gasen, BleV-R-64.284-2. Battelle Institut, 1982.

H. Schilling, Diebold, M., Rother, C., and Jähne, B., “Trust your Model: Light Field Depth Estimation with inline Occlusion Handling”, CVPR. Proceedings. 2018.

Technical Report (5.46 MB)

H. Schilling, Diebold, M., Rother, C., and Jähne, B., “Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2018, pp. 4530–4538.

B. Jähne and Riemer, K., “Two-dimensional wave number spectra of small-scale water surface waves”, J. Geophys. Res., vol. 95, p. 11531--11646, 1990.

S. Hader and Hamprecht, F. A., “Two-Stage Classification with Automatic Feature Selection for an Industrial Application”, Classification, the ubiquitous challenge: Proceedings of GfKl 2004. Springer, pp. 137-144, 2004.

Technical Report (518.16 KB)

W. Peckar, Schnörr, C., Rohr, K., and Stiehl, H. S., “Two-Step Parameter-Free Elastic Image Registration with Prescribed Point Displacements”, in Proc. 9th Int. Conf. on Image Analysis and Processing (ICIAP'97), Florence, Italy, 1997.

U

S. Damrich and Hamprecht, F. H., “UMAP does not reproduce high-dimensional similarities due to negative sampling”. arXiv preprint, 2021.

S. Damrich and Hamprecht, F. A., “On UMAP's True Loss Function”, NeurIPS. Proceedings, vol. 34. 2021.

Technical Report (1.87 MB)

E. Brachmann, Michel, F., Krull, A., Yang, M. Ying, Gumhold, S., and Rother, C., “Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016, vol. 2016-Decem, pp. 3364–3372.

E. Brachmann, Michel, F., Krull, A., Yang, M. Ying, Gumhold, S., and Rother, C., “Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016, vol. 2016-Decem, pp. 3364–3372.

D. Richmond, Kainmueller, D., Glocker, B., Rother, C., and Myers, G., “Uncertainty-driven forest predictors for vertebra localization and segmentation”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9349. pp. 653–660, 2015.

M. Bellagente, Haußmann, M., Luchmann, M., and Plehn, T., “Understanding Event-Generation Networks via Uncertainties”. arXiv preprint, 2021.

A. Blattmann, Milbich, T., Dorkenwald, M., and Ommer, B., “Understanding Object Dynamics for Interactive Image-to-Video Synthesis”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.

D. S. Kirk, Sellen, A. J., Rother, C., and Wood, K. R., “Understanding photowork”, in Conference on Human Factors in Computing Systems - Proceedings, 2006, vol. 2, pp. 761–770.

A. Lifermann, Jähne, B., and Ramamonjiarisoa, A., “Une ètude en soufflerie de la rèflexion des hyperfrèquences par des champs de houles et de vagues”, Oceanologia Acta, vol. SP, p. 15--22, 1987.

C. Schnörr, “Unique Reconstruction of Piecewise Smooth Images by Minimizing Strictly Convex Non-Quadratic Functionals”, vol. 4, pp. 189–198, 1994.

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”, preprint: arXiv, 2019.

B. Brattoli, Büchler, U., Dorkenwald, M., Reiser, P., Filli, L., Helmchen, F., Wahl, A. - S., and Ommer, B., “Unsupervised behaviour analysis and magnification (uBAM) using deep learning”, Nature Machine Intelligence, 2021.

J. Keuchel, Schnörr, C., Schellewald, C., and Cremers, D., “Unsupervised Image Partitioning with Semidefinite Programming”, in Pattern Recognition, Proc. 24th DAGM Symposium, Zürich, Switzerland, 2002, vol. 2449, pp. 141–149.

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.

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.

M. Zisler, Zern, A., Petra, S., and Schnörr, C., “Unsupervised Labeling by Geometric and Spatially Regularized Self-Assignment”, in Proc. SSVM, 2019.

M. Dorkenwald, Büchler, U., and Ommer, B., “Unsupervised Magnification of Posture Deviations Across Subjects”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2020.

article.pdf (1.15 MB)

S. Braun, Esser, P., and Ommer, B., “Unsupervised Part Discovery by Unsupervised Disentanglement”, Proceedings of the German Conference on Pattern Recognition (GCPR) (Oral). Tübingen, 2020.

D. Lorenz, Bereska, L., Milbich, T., and Ommer, B., “Unsupervised Part-Based Disentangling of Object Shape and Appearance”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Oral + Best paper finalist: top 45 / 5160 submissions), 2019.

T. Milbich, Ghori, O., and Ommer, B., “Unsupervised Representation Learning by Discovering Reliable Image Relations”, Pattern Recognition, vol. 102, 2020.

P. Esser, Haux, J., and Ommer, B., “Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis”, in Proceedings of the Intl. Conf. on Computer Vision (ICCV), 2019.

T. Milbich, Bautista, M., Sutter, E., and Ommer, B., “Unsupervised Video Understanding by Reconciliation of Posture Similarities”, in Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017.

H. Lauer, “Untersuchung der Neigungsstatistik von Wasseroberflächenwellen mittels eines schnellen, bildaufnehmenden Verfahrens”. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1998.

M. Beyer, “Untersuchung der Relaxationszeiten von winderzeugten Wasseroberflächenwellen durch periodische Variation der Windgeschwindigkeit”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1993.

U. Schimpf, “Untersuchung des Gasaustausches und der Mikroturbulenz an der Meeresoberfläche mittels Thermographie”. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2000.

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