HCI Logo
Heidelberg University Logo
IWR Logo

Publications

Export 1965 results:
Author [ Title(Asc)] Type Year
Filters: Filter is   [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
V
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 3nd International Conference on Scale Space and Variational Methods in Computer Vision 2011, in press, 2011, vol. 6667, pp. 206-217.
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)
N. Paragios, Faugeras, O., Chan, T., and Schnörr, C., Eds., “Variational, Geometric and Level Sets in Computer Vision (VLSM'05)”, lncs, vol. 3752. Springer, Beijing, China, 2005.
D. Heitz, Mémin, E., and Schnörr, C., “Variational fluid flow measurements from image sequences: synopsis and perspectives”, Exp. Fluids, vol. 48, pp. 369-393, 2010.
D. Heitz, Mémin, E., and Schnörr, C., “Variational fluid flow measurements from image sequences: synopsis and perspectives”, Exp.~Fluids, vol. 48, pp. 369-393, 2010.PDF icon Technical Report (1.91 MB)
P. Ruhnau, Stahl, A., and Schnörr, C., “Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization”, Measurement Science and Technology, vol. 18, pp. 755-763, 2007.PDF icon Technical Report (842.06 KB)
P. Ruhnau, Stahl, A., and Schnörr, C., “Variational Estimation of Experimental Fluid Flows with Physics-Based Spatio-Temporal Regularization”, Measurement Science and Technology, vol. 18, pp. 755-763, 2007.
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.PDF icon Technical Report (3.37 MB)
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, “Variational Correlation and Decomposition Methods for Particle Image Velocimetry”. Heidelberg University, Faculty of Mathematics and Computer Sciences, Heidelberg, Germany, 2009.
M. Haußmann, Hamprecht, F. A., and Kandemir, M., “Variational Bayesian Multiple Instance Learning with Gaussian Processes”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 6570-6579, 2017.PDF icon Technical Report (1.29 MB)
C. Schnörr, “Variational approaches to Image Segmentation and Feature Extraction”. University of Hamburg, Comp. Sci. Dept., Hamburg, Germany, 1998.
A. Vlasenko and Schnörr, C., “Variational Approaches for Model-Based PIV and Visual Fluid Analysis”, Imaging Measurement Methods for Flow Analysis, vol. 106. Springer, pp. 247-256, 2009.
A. Vlasenko and Schnörr, C., “Variational Approaches for Model-Based PIV and Visual Fluid Analysis”, Imaging Measurement Methods for Flow Analysis, vol. 106. Springer, pp. 247-256, 2009.PDF icon Technical Report (3.39 MB)
C. Schnörr, Sprengel, R., and Neumann, B., “A Variational Approach to the Design of Early Vision Algorithms”, Computing Suppl., vol. 11, pp. 149-165, 1996.
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.
P. Ruhnau, Gütter, C., Putze, T., and Schnörr, C., “A variational approach for particle tracking velocimetry”, Meas. Science and Techn., vol. 16, pp. 1449-1458, 2005.
C. Schnörr, “Variational Adaptive Smoothing and Segmentation”, in Computer Vision and Applications: A Guide for Students and Practitioners, San Diego, 2000, pp. 459–482.
F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., “Variational Adaptive Correlation Method for Flow Estimation”, IEEE Transactions on Image Processing, vol. 21, 6, pp. 3053 - 3065, 2011.
F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., “Variational Adaptive Correlation Method for Flow Estimation”, IEEE Transactions on Image Processing, vol. 21, p. 3053 -- 3065, 2012.PDF icon Technical Report (18.81 MB)
F. Becker, Wieneke, B., Petra, S., Schröder, A., and Schnörr, C., “Variational Adaptive Correlation Method for Flow Estimation”, IEEE Transactions on Image Processing, vol. 21, pp. 3053 – 3065, 2012.
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.
U
B. Michael Kelm, Kaster, F. O., Henning, A., Weber, M. - A., Bachert, P., Bösinger, P., Hamprecht, F. A., and Menze, B. H., “Using Spatial Prior Knowledge in the Spectral Fitting of Magnetic Resonance Spectroscopic Images”, NMR in Biomedicine, vol. 25(1), pp. 1-13, 2011.PDF icon Technical Report (1.94 MB)
M. Riedl, “Using Protein Identification Data to Improve Mass Spectrometry Feature Extraction”, University of Heidelberg, 2010.
D. Kotovenko, Sanakoyeu, A., Lang, S., Ma, P., and Ommer, B., “Using a Transformation Content Block For Image Style Transfer”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2019.
P. Kohli, Nickisch, H., Rother, C., and Rhemann, C., “User-centric learning and evaluation of interactive segmentation systems”, International Journal of Computer Vision, vol. 100, pp. 261–274, 2012.
H. G. Tremmel, “Untersuchungen zur Wiederbelüftung von Neckar und Rhein mit der Konstantflußmethode”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1989.
K. Degreif, “Untersuchungen zum Gasaustausch - Entwicklung und Applikation eines zeitlich aufgelösten Massenbilanzverfahrens”. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2006.

Pages