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P. Libner, “Entwicklung eines optische Systems zur Erfassung von Wellenparametern bei Feldmessungen im Hinblick auf den Gasaustausch”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1984.
P. Libner, Jähne, B., and Plate, E. J., “Ein neue Methode zur lokalen und momentanen Bestimmung der Wiederbelüftungsraten von Gewässern”, Wasserwirtschaft, vol. 77, p. 230--235, 1987.
J. Li, “Robust Single Object Tracking via Fully Convolutional Siamese Networks”, Heidelberg University, 2019.
Y. Li, “Semantic Instance Segmentation with the Multiway Mutex Watershed”, Heidelberg University, 2019.
W. Li, Hosseini Jafari, O., and Rother, C., “Localizing Common Objects Using Common Component Activation Map”, 2019.
W. Li, Hosseini Jafari, O., and Rother, C., “Deep Object Co-segmentation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11363 LNCS, pp. 638–653.
E. Levinkov, Uhrig, J., Tang, S., Omran, M., Insafutdinov, E., Kirillov, A., Rother, C., Brox, T., Schiele, B., and Andres, B., “Joint graph decomposition & node labeling: Problem, algorithms, applications”, in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017, vol. 2017-Janua, pp. 1904–1912.
C. Leue, “Quantitative Analyse von NOx - Emissionen aus GOME Satellitenbildfolgen”. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1999.
C. Leue, “Ein Verfahren zur Segmentierung von Partikelbildern in der Strömungsvisualisierung”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1996.
C. Leue, Geißler, P., Jähne, B., Jähne, B., Geißler, P., and Haußecker, H., “Segmentierung von Partikelbildern in der Strömungsvisualisierung”, in Proceedings of 18th DAGM-Symposium Mustererkennung, 1996, p. 118--129.
C. Leue, Wenig, M., Platt, U., Jähne, B., Geißler, P., and Haußecker, H., “Retrieval of Atmospheric Trace Gas Concentrations”, Handbook of Computer Vision and Applications, vol. 3: Systems and Applications. Academic Press, pp. 783-805, 1999.
C. Leue, Wenig, M., Jähne, B., and Platt, U., “Quantitative observation of biomass-burning plumes from GOME”, ESA Publications EOQ, vol. 58, p. 33--35, 1998.
C. Leue, Wenig, M., Jähne, B., and Platt, U., “GOME mißt atmosphärische Stickoxide. Globale Biomassenverbrennung und Industrieemissionen”, Physik in unserer Zeit, vol. 29, p. 179, 1998.
C. Leue, Wenig, M., Platt, U., Jähne, B., and Haußecker, H., “NOX Emissions Retrieved from Satellite Images”, Computer Vision and Applications. A Guide for Students and Practitioners. Academic Press, p. 654--655, 2000.
C. Leue, Wenig, M., Wagner, T., Klimm, O., Platt, U., and Jähne, B., “Quantitative analysis of NO$_x$ emissions from Global Ozone Monitoring Experiment satellite image sequences”, J. Geophys. Res., vol. 106, p. 5493--5505, 2001.
K. Lerch, “Discontinuity Preserving Filtering of Spectral Images”, University of Heidelberg, 2006.
F. Lenzen and Berger, J., “Solution-Driven Adaptive Total Variation Regularization”, in LNCS, 2015.PDF icon Technical Report (857.29 KB)
F. Lenzen, Becker, F., and Lellmann, J., “Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities”, in Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision SSVM, 2013, vol. 7893, pp. 61-73.
F. Lenzen, Becker, F., Lellmann, J., Petra, S., and Schnörr, C., “A Class of Quasi-Variational Inequalities for Adaptive Image Denoising and Decomposition”, Computational Optimization and Applications (COAP), vol. 54 (2), pp. 371-398, 2013.
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, Kim, K. I., Schäfer, H., Nair, R., Meister, S., Becker, F., and Garbe, C. S., “Denoising Strategies for Time-of-Flight Data”, in Time-of-Flight Imaging: Algorithms, Sensors and Applications, 2013, vol. 8200, pp. 24-25.
F. Lenzen, Lellmann, J., Becker, F., and Schnörr, C., “Solving QVIs for Image Restoration with Adaptive Constraint Sets”, SIAM Journal on Imaging Sciences (SIIMS), in press, 2014.
F. Lenzen, Schäfer, H., and Garbe, C. S., “Denoising Time-Of-Flight Data with Adaptive Total Variation”, in Proceedings ISVC, 2011, pp. 337-346.
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 and Berger, J., “Solution-Driven Adaptive Total Variation Regularization”, in LNCS, 2015.
F. Lenzen, Lellmann, J., Becker, F., and Schnörr, C., “Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets”, SIAM J. Imag. Sci., vol. 7, pp. 2139–2174, 2014.
F. Lenzen, Becker, F., and Lellmann, J., “Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities”, in Proceedings of the 4th International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) 2013, 2013, vol. 54, no. 2, p. 371--398.PDF icon Technical Report (702.08 KB)
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., “A class of quasi-variational inequalities for adaptive image denoising and decomposition”, Computational Optimization and Applications, vol. 54, pp. 371-398, 2013.PDF icon Technical Report (748.66 KB)
F. Lenzen, Kim, K. In, Schäfer, H., Nair, R., Meister, S., Becker, F., and Garbe, C. S., “Denoising Strategies for Time-of-Flight Data”, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, vol. 8200. Springer, pp. 25-45, 2013.PDF icon Technical Report (961.62 KB)
F. Lenzen, Lellmann, J., Becker, F., and Schnörr, C., “Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets”, SIAM J.~Imag.~Sci., vol. 7, p. 2139--2174, 2014.PDF icon Technical Report (802.13 KB)
S. Lenor, “Model-Based Estimation of Meteorological Visibility in the Context of Automotive Camera Systems”, vol. Dissertation. IWR, Univ. Heidelberg, 2016.
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.
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.

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