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Author Title Type [ Year(Asc)]
2013
S. Wanner, Straehle, C. N., and Goldlücke, B., “Globally Consistent Multi-Label Assignment on the Ray Space of 4D Light Fields”, CVPR 2013. Proceedings, pp. 1011-1018, 2013.
S. Wanner, Straehle, C. N., and Goldlücke, B., “Globally consistent multi-label assignment on the ray space of 4D light fields”, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
B. Schmitzer and Schnörr, C., “A Hierarchical Approach to Optimal Transport”, in Scale Space and Variational Methods (SSVM 2013), 2013, pp. 452-464.
V. Vineet, Rother, C., and Torr, P. H. S., “Higher order priors for joint intrinsic image, objects, and attributes estimation”, in Advances in Neural Information Processing Systems, 2013.
J. H. Kappes, Speth, M., Reinelt, G., and Schnörr, C., “Higher-order Segmentation via Multicuts”, ArXiv e-prints. 2013.PDF icon Technical Report (1.07 MB)
J. Hendrik Kappes, Speth, M., Reinelt, G., and Schnörr, C., “Higher-order Segmentation via Multicuts”, ArXiv e-prints. 2013.
J. Horn, “Hochaufgelöste optische Wellenhöhenmessung am Aeolotron mit Laser-induzierter Fluoreszenz”, Institut für Umwelphysik, Univeristät Heidelberg, Germany, 2013.
P. Fahle, “Hochauflösende Messung der raumzeitlichen Variation der Neigung winderzeugter Wasserwellen”, Institut für Umwelphysik, Univeristät Heidelberg, Germany, 2013.
A. Donath and Kondermann, D., “How Good is Crowdsourcing for Optical Flow Ground Truth Generation?”, submitted to CVPR, 2013.
M. Geese, “Image Sensor Nonuniformity Correction by a Scene-Based Maximum Likelihood Approach”. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2013.
M. Geese, “Image Sensor Nonuniformity Correction by a Scene-Based Maximum Likelihood Approach”, vol. Dissertation. IWR, Univ. Heidelberg, 2013.
F. Friedl, “Investigating the Transfer of Oxygen at the Wavy Air-Water Interface under Wind-Induced Turbulence”, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2013.
L. Fiaschi, Grosser, K. - H., Afonso, B., Zlatic, M., and Hamprecht, F. A., “Keeping Count: Leveraging Temporal Context to Count Heavily Overlapping Objects”, ISBI 2013.Proceedings, pp. 656-659, 2013.PDF icon Technical Report (711.68 KB)
C. N. Straehle, Peter, S., Köthe, U., and Hamprecht, F. A., “K-smallest Spanning Tree Segmentations”, in German Conference on Pattern Recognition (DAGM/GCPR). Proceedings, 2013, pp. 375-384.PDF icon Technical Report (1.18 MB)
K. E. Krall, “Laboratory Investigations of Air-Sea Gas Transfer under a Wide Range of Water Surface Conditions”, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2013.
R. Walecki, “Large-Scale Automatic Reconstruction of Myelianated Axons and Detection of the Nodes of Ranvier”, University of Heidelberg, 2013.
L. Fiaschi, “Learning Based Biological Image Analysis”. University of Heidelberg, 2013.
J. Jancsary, Nowozin, S., and Rother, C., “Learning convex QP relaxations for structured prediction”, in 30th International Conference on Machine Learning, ICML 2013, 2013, pp. 1952–1960.
F. Diego and Hamprecht, F. A., “Learning Multi-Level Sparse Representation”, in NIPS. Proceedings, 2013.PDF icon Technical Report (2.79 MB)
F. Diego and Hamprecht, F. A., “Learning Multi-Level Sparse Representation for Identifying Neuronal Activity”, in Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS). Book of Abstracts., 2013.PDF icon Technical Report (1.05 MB)
T. Kröger, Mikula, S., Denk, W., Köthe, U., and Hamprecht, F. A., “Learning to Segment Neurons with Non-local Quality Measures”, in MICCAI 2013. Proceedings, part II, 2013, vol. 8150, pp. 419-427.PDF icon Technical Report (2.87 MB)
B. Antic, Milbich, T., and Ommer, B., “Less is More: Video Trimming for Action Recognition”, in Proceedings of the IEEE International Conference on Computer Vision, Workshop on Understanding Human Activities: Context and Interaction, 2013, p. 515--521.PDF icon Technical Report (984.89 KB)
B. Schmitzer and Schnörr, C., “Modelling convex shape priors and matching based on the Gromov-Wasserstein distance”, Journal of Mathematical Imaging and Vision, vol. 46, pp. 143-159, 2013.PDF icon Technical Report (957.78 KB)
B. Schmitzer and Schnörr, C., “Modelling convex shape priors and matching based on the Gromov-Wasserstein distance”, Journal of Mathematical Imaging and Vision, vol. 46, pp. 143-159, 2013.
A. Monroy, Bell, P., and Ommer, B., “A Morphometric Approach to Reception Analysis of Premodern Art”, in Scientific Computing & Cultural Heritage, 2013.PDF icon Technical Report (17.75 MB)
M. Becker, Baron, M., Kondermann, D., Bussler, M., and Helzle, V., “Movie Dimensionalization Via Sparse User Annotations”, in submitted to 3DTV-Con, 2013.
D. Kondermann and Becker, M., “Movie Dimensionalization Via Sparse User Annotations”, in submitted to ICCV, 2013.
P. Bell, Schlecht, J., and Ommer, B., “Nonverbal Communication in Medieval Illustrations Revisited by Computer Vision and Art History”, Visual Resources Journal, Special Issue on Digital Art History, vol. 29, p. 26--37, 2013.
B. Schmitzer and Schnörr, C., “Object Segmentation by Shape Matching with Wasserstein Modes”, in Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2013), 2013, pp. 123-136.
D. Kiefhaber, Rocholz, R., Bauer, P. Salomon, and Jähne, B., “Optical measurement of surface ocean waves”, in 3rd EOS Topical Meeting on Blue Photonics --- Optics in the Sea, 2013.
M. Atif, “Optimal Depth Estimation and Extended Depth of Field from Single Images by Computational Imaging using Chromatic Aberrations”. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2013.
M. Atif, “Optimal Depth Estimation and Extended Depth of Field from Single Images by Computational Imaging using Chromatic Aberrations”, vol. Dissertation. IWR, Univ. Heidelberg, 2013.
M. Atif and Jähne, B., “Optimal Depth Estimation from a Single Image by Computational Imaging Using Chromatic Aberrations”, tm --- Technisches Messen, vol. 80, p. 343--348, 2013.
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.
C. S. Garbe and Ommer, B., “Parameter Estimation in Image Processing and Computer Vision”, in Model Based Parameter Estimation: Theory and Applications, Springer, 2013, p. 311--334.PDF icon Technical Report (928 KB)

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