HCI Logo
Heidelberg University Logo
IWR Logo

Publications

Export 1965 results:
Author Title [ Type(Asc)] Year
Conference Paper
F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., “Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences”, in 2011 IEEE International Conference on Computer Vision (ICCV), 2011, pp. 1692 – 1699.
F. Becker, Lenzen, F., Kappes, J. H., and Schnörr, C., “Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences”, in 2011 IEEE International Conference on Computer Vision (ICCV), 2011, p. 1692 -- 1699.PDF icon Technical Report (4.9 MB)
F. Savarino and Schnörr, C., “A Variational Perspective on the Assignment Flow”, in Proc. SSVM, 2019.
C. Schnörr, “Variational Methods for Adaptive Image Smoothing and Segmentation”, in Handbook on Computer Vision and Applications: Signal Processing and Pattern Recognition, San Diego, 1999, vol. 2, pp. 451–484.
P. Swoboda and Schnörr, C., “Variational Image Segmentation and Cosegmentation with the Wasserstein Distance”, in Energy Minimization Methods in Computer Vision and Pattern Recognition, 2013, vol. 8081, pp. 321–334.
P. Swoboda and Schnörr, C., “Variational Image Segmentation and Cosegmentation with the Wasserstein Distance”, in Energy Minimization Methods in Computer Vision and Pattern Recognition, 2013, vol. 8081, p. 321--334.PDF icon Technical Report (8.06 MB)
C. Schnörr and Weickert, J., “Variational Image Motion Computation: Theoretical Framework, Problems and Perspectives”, in Mustererkennung 2000, Kiel, Germany, 2000.
F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “Variational Image Denoising with Adaptive Constraint Sets”, in Proceedings of the 3rd International Conference on Scale Space and Variational Methods in Computer Vision 2011, 2012, pp. 206-217.
F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “Variational Image Denoising with Adaptive Constraint Sets”, in LNCS, 2012, pp. 206-217.PDF icon Technical Report (649.03 KB)
F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “Variational Image Denoising with Adaptive Constraint Sets”, in Proceedings of the 3nd International Conference on Scale Space and Variational Methods in Computer Vision 2011, in press, 2011, vol. 6667, pp. 206-217.
T. Kohlberger, Mémin, E., and Schnörr, C., “Variational Dense Motion Estimation Using the Helmholtz Decomposition”, in Scale Space Methods in Computer Vision, 2003, vol. 2695, pp. 432–448.
F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “Variational Correlation Approach to Flow Measurement with Window Adaption”, in 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2008, p. 1.1.3.
F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “Variational Correlation Approach to Flow Measurement with Window Adaption”, in 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2008, p. 1.1.8.
F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “Variational Correlation Approach to Flow Measurement with Window Adaption”, in 14th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2008, p. 1.1.3.PDF icon Technical Report (3.37 MB)
A. Telea, Preußer, T., Garbe, C. S., Droske, M., and Rumpf, M., “A variational approach to joint denoising, edge detection and motion estimation”, in Proceedings of the 28th DAGM Symposium on Pattern Recognition, 2006, p. 525--535.
F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 335--344.PDF icon Technical Report (1.82 MB)
F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry"”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, pp. 335-344.
F. Becker, Wieneke, B., Yuan, J., and Schnörr, C., “A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry”, in Pattern Recognition – 30th DAGM Symposium, 2008, vol. 5096, pp. 335–344.
C. Schnörr, “Variational Adaptive Smoothing and Segmentation”, in Computer Vision and Applications: A Guide for Students and Practitioners, San Diego, 2000, pp. 459–482.
N. M. Frew, Bock, E. J., McGilles, W. R., Karachintsev, A., Hara, T., Münsterer, T., Jähne, B., and Jähne, B., “Variation of air--water gas transfer with wind stress and surface viscoelasticity”, in Air-water Gas Transfer, Selected Papers from the Third International Symposium on Air-Water Gas Transfer, 1995, p. 529--541.
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.
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.
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.
M. Zisler, Zern, A., Petra, S., and Schnörr, C., “Unsupervised Labeling by Geometric and Spatially Regularized Self-Assignment”, in Proc. SSVM, 2019.
A. Zern, Zisler, M., Aström, F., Petra, S., and Schnörr, C., “Unsupervised Label Learning on Manifolds by Spatially Regularized Geometric Assignment”, in GCPR, 2018.
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.
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.
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.
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.
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. 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.
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.
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.
S. Lenor, Martini, J., Jähne, B., Stopper, U., Weber, S., and Ohr, F., “Tracking-based visibility estimation”, in Pattern Recognition, 36th German Conference, GCPR 2014, Münster, Germany, September 2-5, 2014, 2014, vol. 8753, p. 365--376.

Pages