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Publications

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Author Title [ Type(Asc)] Year
Conference Paper
Becker, F, Lenzen, F, Kappes, J H and Schnörr, C (2011). Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences. 2011 IEEE International Conference on Computer Vision (ICCV). 1692 – 1699
Becker, F, Lenzen, F, Kappes, J H and Schnörr, C (2011). Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences. 2011 IEEE International Conference on Computer Vision (ICCV). 1692 -- 1699PDF icon Technical Report (4.9 MB)
Savarino, F and Schnörr, C (2019). A Variational Perspective on the Assignment Flow. Proc. SSVM. Springer
Schnörr, (1999). Variational Methods for Adaptive Image Smoothing and Segmentation. Handbook on Computer Vision and Applications: Signal Processing and Pattern Recognition. Academic Press, San Diego. 2 451–484
Swoboda, P and Schnörr, C (2013). Variational Image Segmentation and Cosegmentation with the Wasserstein Distance. Energy Minimization Methods in Computer Vision and Pattern Recognition. Springer. 8081 321–334
Swoboda, P and Schnörr, C (2013). Variational Image Segmentation and Cosegmentation with the Wasserstein Distance. Energy Minimization Methods in Computer Vision and Pattern Recognition. Springer. 8081 321--334PDF icon Technical Report (8.06 MB)
Schnörr, C and Weickert, J (2000). Variational Image Motion Computation: Theoretical Framework, Problems and Perspectives. Mustererkennung 2000. Springer, Kiel, Germany
Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2012). Variational Image Denoising with Adaptive Constraint Sets. Proceedings of the 3rd International Conference on Scale Space and Variational Methods in Computer Vision 2011. Springer. 206-217
Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2012). Variational Image Denoising with Adaptive Constraint Sets. LNCS. Springer. 206-217PDF icon Technical Report (649.03 KB)
Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2011). Variational Image Denoising with Adaptive Constraint Sets. Proceedings of the 3nd International Conference on Scale Space and Variational Methods in Computer Vision 2011, in press. Springer. 6667 206-217
Kohlberger, T, Mémin, E and Schnörr, C (2003). Variational Dense Motion Estimation Using the Helmholtz Decomposition. Scale Space Methods in Computer Vision. Springer. 2695 432–448
Becker, F, Wieneke, B, Yuan, J and Schnörr, C (2008). Variational Correlation Approach to Flow Measurement with Window Adaption. 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics. 1.1.3
Becker, F, Wieneke, B, Yuan, J and Schnörr, C (2008). Variational Correlation Approach to Flow Measurement with Window Adaption. 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics. 1.1.8
Becker, F, Wieneke, B, Yuan, J and Schnörr, C (2008). Variational Correlation Approach to Flow Measurement with Window Adaption. 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics. 1.1.3PDF icon Technical Report (3.37 MB)
Telea, A, Preußer, T, Garbe, C S, Droske, M and Rumpf, M (2006). A variational approach to joint denoising, edge detection and motion estimation. Proceedings of the 28th DAGM Symposium on Pattern Recognition. 525--535. http://numod.ins.uni-bonn.de/research/papers/public/PrDrGa06.pdf
Becker, F, Wieneke, B, Yuan, J and Schnörr, C (2008). A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry. Pattern Recognition -- 30th DAGM Symposium. Springer Verlag. 5096 335--344PDF icon Technical Report (1.82 MB)
Becker, F, Wieneke, B, Yuan, J and Schnörr, C (2008). A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry". Pattern Recognition -- 30th DAGM Symposium. 5096 335-344
Becker, F, Wieneke, B, Yuan, J and Schnörr, C (2008). A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry. Pattern Recognition – 30th DAGM Symposium. Springer Verlag. 5096 335–344
Schnörr, (2000). Variational Adaptive Smoothing and Segmentation. Computer Vision and Applications: A Guide for Students and Practitioners. Academic Press, San Diego. 459–482
Frew, N M, Bock, E J, McGilles, W R, Karachintsev, A, Hara, T, Münsterer, T, Jähne, B and Jähne, B (1995). Variation of air--water gas transfer with wind stress and surface viscoelasticity. Air-water Gas Transfer, Selected Papers from the Third International Symposium on Air-Water Gas Transfer. AEON. 529--541
Milbich, T, Bautista, M, Sutter, E and Ommer, B (2017). Unsupervised Video Understanding by Reconciliation of Posture Similarities. Proceedings of the IEEE International Conference on Computer Vision (ICCV). https://hciweb.iwr.uni-heidelberg.de/compvis/research/tmilbich_iccv17
Esser, P, Haux, J and Ommer, B (2019). Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis. Proceedings of the Intl. Conf. on Computer Vision (ICCV). https://compvis.github.io/robust-disentangling/
Lorenz, D, Bereska, L, Milbich, T and Ommer, B (2019). Unsupervised Part-Based Disentangling of Object Shape and Appearance. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Oral + Best paper finalist: top 45 / 5160 submissions)
Zisler, M, Zern, A, Petra, S and Schnörr, C (2019). Unsupervised Labeling by Geometric and Spatially Regularized Self-Assignment. Proc. SSVM. Springer
Zern, A, Zisler, M, Aström, F, Petra, S and Schnörr, C (2018). Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment. GCPR
Keuchel, J, Schnörr, C, Schellewald, C and Cremers, D (2002). Unsupervised Image Partitioning with Semidefinite Programming. Pattern Recognition, Proc. 24th DAGM Symposium. Springer, Zürich, Switzerland. 2449 141–149
Kirk, D S, Sellen, A J, Rother, C and Wood, K R (2006). Understanding photowork. Conference on Human Factors in Computing Systems - Proceedings. 2 761–770
Brachmann, E, Michel, F, Krull, A, Yang, M Ying, Gumhold, S and Rother, C (2016). Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2016-Decem 3364–3372
Brachmann, E, Michel, F, Krull, A, Yang, M Ying, Gumhold, S and Rother, C (2016). Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2016-Decem 3364–3372
Peckar, W, Schnörr, C, Rohr, K and Stiehl, H S (1997). Two-Step Parameter-Free Elastic Image Registration with Prescribed Point Displacements. Proc. 9th Int. Conf. on Image Analysis and Processing (ICIAP'97). Florence, Italy
Schilling, H, Diebold, M, Rother, C and Jähne, B (2018). Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 4530–4538
Glocker, B, T. Heibel, H, Navab, N, Kohli, P and Rother, C (2010). TriangleFlow: Optical flow with triangulation-based higher-order likelihoods. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6313 LNCS 272–285. http://vision.middlebury.edu/flow/
Garbe, C S, Flatow, F, Klinger, M, Schepanski, K, Tegen, I and Rannacher, R (2009). Transport of Sahara dust into the Atlantic Ocean from satellite image sequence analysis. SOLAS Open Science Conference. 27
Garbe, C S, Flatow, F, Klinger, M, Schepanski, K, Tegen, I and Rannacher, R (2009). Transport of dust across the Sahara from satellite image sequence analysis. Eos Transactions. 90 EP21A-0565
Lenor, S, Martini, J, Jähne, B, Stopper, U, Weber, S and Ohr, F (2014). Tracking-based visibility estimation. Pattern Recognition, 36th German Conference, GCPR 2014, Münster, Germany, September 2-5, 2014. Springer. 8753 365--376

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