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S. Lang and Ommer, B., “Transforming Information Into Knowledge: How Computational Methods Reshape Art History”, Digital Humanities Quaterly (DHQ), vol. 15, no. 3, 2021.

P. A. Lange, Jähne, B., Tschiersch, J., and Ilmberger, J., “Comparison between an amplitude-measuring wire and a slope-measuring laser water wave gauge”, Rev. Sci. Instrum., vol. 53, p. 651--655, 1982.

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

H. Lauer, “Messung der Neigungsverteilung von Wasseroberflächenwellen mittels digitaler Bilverarbeitung”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1994.

F. Lauer and Schnörr, C., “Spectral Clustering of Linear Subspaces for Motion Segmentation”, in Proc. IEEE Int. Conf. Computer Vision (ICCV'09), Kyoto, Japan, 2009.

F. Lauer, Bloch, G., and Vidal, R., “A Continuous Optimization Framework for Hybrid System Identification”, in submitted to Automatica, 2009.

F. Lauer and Schnörr, C., “Spectral Clustering of Linear Subspaces for Motion Segmentation”, in Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan, in press, 2009, pp. 678-685.

F. Lauer and Schnörr, C., “Spectral Clustering of Linear Subspaces for Motion Segmentation”, in Proc.~IEEE Int.~Conf.~Computer Vision (ICCV'09), 2009.

Technical Report (1.12 MB)

D. Lefloch, Nair, R., Lenzen, F., Schäfer, H., Streeter, L., Cree, M. J., Koch, R., and Kolb, A., “Technical Foundation and Calibration Methods for Time-of-Flight Cameras”, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, vol. 8200. Springer, pp. 3-24, 2013.

D. Lefloch, Nair, R., Lenzen, F., Schäfer, H., Streeter, L., and Cree, M. J., “Technical Foundation and Calibration Methods for Time-of-Flight Cameras”, in Time-of-Flight Imaging: Algorithms, Sensors and Applications, 2013, vol. 8200.

T. Leistner, Schilling, H., Mackowiak, R., Gumhold, S., and Rother, C., “Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift”, in Proceedings - 2019 International Conference on 3D Vision, 3DV 2019, 2019, pp. 249–257.

PDF (8.94 MB)

M. Lell, “Ortsaufgelöste Bestimmung von Blattwachstum durch Strukturanalyse von Bildsequenzen aus dem nahen Infrarot”, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1996.

J. Lellmann, Breitenreicher, D., and Schnörr, C., “Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision”, in European Conference on Computer Vision (ECCV), 2010, vol. 6312, pp. 494–505.

J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, in Energy Min. Meth. Comp. Vis. Patt. Recogn., 2011, vol. 6819, pp. 132–146.

J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, IPA group, Heidelberg University, 2011.

J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, Journal of Mathematical Imaging and Vision, vol. 47, pp. 239-257, 2012.

J. Lellmann and Schnörr, C., “Continuous Multiclass Labeling Approaches and Algorithms”, CoRR, vol. abs/1102.5448, 2011.

J. Lellmann and Schnörr, C., “Regularizers for Vector-Valued Data and Labeling Problems in Image Processing”, Control Systems and Computers, vol. 2, pp. 43–54, 2011.

J. Lellmann and Schnörr, C., “Continuous Multiclass Labeling Approaches and Algorithms”, Univ. of Heidelberg, 2010.

J. Lellmann, Becker, F., and Schnörr, C., “Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers”, in IEEE International Conference on Computer Vision (ICCV), 2009, p. 646 -- 653.

Technical Report (930.18 KB)

J. Lellmann, Breitenreicher, D., and Schnörr, C., “Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision”, in European Conference on Computer Vision (ECCV), 2010, vol. 6312, p. 494--505.

Technical Report (1.94 MB)

J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.

Technical Report (1.75 MB)

J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, IWR, University of Heidelberg, 2008.

Technical Report (2.6 MB)

J. Lellmann, Lellmann, B., Widmann, F., and Schnörr, C., “Discrete and Continuous Models for Partitioning Problems”, Int.~J.~Comp.~Visionz, vol. 104, pp. 241-269, 2013.

Technical Report (4.74 MB)

J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, in Energy Min. Meth. Comp. Vis. Patt. Recogn., 2011, vol. 6819, p. 132--146.

Technical Report (1 MB)

J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, Journal of Mathematical Imaging and Vision, vol. 47, pp. 239-257, 2012.

Technical Report (616.16 KB)

J. Lellmann and Schnörr, C., “Continuous Multiclass Labeling Approaches and Algorithms”, SIAM J.~Imag.~Sci., vol. 4, pp. 1049-1096, 2011.

Technical Report (4.31 MB)

J. Lellmann, Becker, F., and Schnörr, C., “Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers”, in Proceedings of the IEEE Conference on Computer Vision (ICCV 09) Kyoto, Japan, 2009, pp. 646-653.

J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., Schnörr, C., Mórken, K., and Lysaker, M., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.

J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, Journal of Mathematical Imaging and Vision, vol. 47 (3), pp. 239-257, 2013.

J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for Variational Relaxations of Optimal Partition Problems”, 2010.

J. Lellmann, Lenzen, F., and Schnörr, C., “Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem”, in Energy Min. Meth. Comp. Vis. Patt. Recogn., 2011, pp. 132-146.

V. Lempitsky, Rother, C., Roth, S., and Blake, A., “Fusion moves for markov random field optimization”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, pp. 1392–1405, 2010.

V. Lempitsky, Rother, C., Roth, S., and Blake, A., “Fusion moves for markov random field optimization”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, pp. 1392–1405, 2010.

V. Lempitsky, Blake, A., and Rother, C., “Branch-and-mincut: Global optimization for image segmentation with high-level priors”, Journal of Mathematical Imaging and Vision, vol. 44, pp. 315–329, 2012.

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