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Publications

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Author Title Type [ Year(Asc)]
2014
M. Hoai, Torresani, L., De La Torre, F., and Rother, C., “Learning discriminative localization from weakly labeled data”, in Pattern Recognition, 2014, vol. 47, pp. 1523–1534.
B. Antic and Ommer, B., “Learning Latent Constituents for Recognition of Group Activities in Video”, in Proceedings of the European Conference on Computer Vision (ECCV) (Oral), 2014, p. 33--47.PDF icon Technical Report (4.54 MB)
T. Kröger, “Learning-based Segmentation for Connectomics”. University of Heidelberg, 2014.
M. Bopp, “Luft- und wasserseitige Strömungsverhältnisse im ringförmigen Heidelberger Wind-Wellen-Kanal (Aeolotron)”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2014.
M. Bopp, “Luft- und wasserseitige Strömungsverhältnisse im ringförmigen Heidelberger Wind-Wellen-Kanal (Aeolotron)”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2014.
J. Hendrik Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in International Workshop on Graphical Models in Computer Vision, 2014.
J. H. Kappes, Beier, T., and Schnörr, C., “MAP-Inference on Large Scale Higher-Order Discrete Graphical Models by Fusion Moves”, in Computer Vision - {ECCV} 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part {II}, 2014.PDF icon Technical Report (557.49 KB)
D. Kiefhaber, Zappa, C. J., and Jähne, B., “Measurement of wind waves statistics from specular reflections”, in Ocean Science Meeting, 23--28. 02. 2014, Honolulu Hawaii, 2014.
E. Mesarchaki, Kräuter, C., Krall, K. Ellen, Bopp, M., Helleis, F., Williams, J., and Jähne, B., “Measuring air-sea gas exchange velocities in a large scale annular wind-wave tank”, Ocean Sci. Discuss., vol. 11, p. 1643--1689, 2014.
H. Schäfer, Lenzen, F., and Garbe, C. S., “Model based scattering correction in time-of-flight cameras”, Optics Express, vol. 22, pp. 29835-29846, 2014.
A. Monroy, Bell, P., and Ommer, B., “Morphological Analysis for Investigating Artistic Images”, Image and Vision Computing, vol. 32, p. 414--423, 2014.PDF icon Technical Report (2.86 MB)
G. Urban, Bendszus, M., Hamprecht, F. A., and Kleesiek, J., “Multi-modal Brain Tumor Segmentation using Deep Convolutional NeuralNetworks”, in MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, winningcontribution, 2014, pp. 31-35.
M. Wieler, “Multiple Instance Learning with Random Forests and Applications in Industrial Optical Inspection”. University of Heidelberg, 2014.
C. N. Straehle, Kandemir, M., Köthe, U., and Hamprecht, F. A., “Multiple instance learning with response-optimized random forests”, in ICPR. Proceedings, 2014, pp. 3768 - 3773.PDF icon Technical Report (296.66 KB)
M. Kandemir, Klami, A., Gonen, M., Vetek, A., and Kaski, S., “Multi-task and multi-view learning of user state”, Neurocomputing, vol. 139, pp. 97-106, 2014.
G. Urban, “Neural Networks: Optimization and Applications”, University of Heidelberg, 2014.
P. Márquez-Neila, Kohli, P., Rother, C., and Baumela, L., “Non-parametric higher-order random fields for image segmentation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, vol. 8694 LNCS, pp. 269–284.
M. Takami, Bell, P., and Ommer, B., “Offline Learning of Prototypical Negatives for Efficient Online Exemplar SVM”, in Winter Conference on Applications of Computer Vision, 2014, p. 377--384.
F. Becker, Petra, S., and Schnörr, C., “Optical Flow”, Handbook of Mathematical Methods in Imaging. Springer, 2014.
D. Kiefhaber, “Optical Measurement of Short Wind Waves --- from the Laboratory to the Field”, vol. Dissertation. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2014.
F. Jug, Pietzsch, T., Kainmüller, D., Funke, J., Kaiser, M., van Nimwegen, E., Rother, C., and Myers, G., “Optimal joint segmentation and tracking of escherichia coli in the mother machine”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8677, pp. 25–36, 2014.
S. Wanner, “Orientation Analysis in 4D Light Fields”, vol. Dissertation. IWR, Univ. Heidelberg, 2014.
S. Wanner, “Orientation Analysis in 4D Light Fields”. IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 2014.
J. Yarkony, Beier, T., Baldi, P., and Hamprecht, F. A., “Parallel Multicut Segmentation via Dual Decomposition”, in New Frontiers in Mining Complex Patterns - Third International Workshop, {NFMCP} 2014, Held in Conjunction with {ECML-PKDD} 2014, Nancy, France, September 19, 2014, Revised Selected Papers, 2014.
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Partial Optimality by Pruning for MAP-inference with General GraphicalModels”, CVPR. Proceedings. pp. 1170-1177, 2014.
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Partial Optimality by Pruning for MAP-inference with General Graphical Models”, in IEEE Conference on Computer Vision and Pattern Recognition 2014, 2014.PDF icon Technical Report (703.34 KB)
P. Swoboda, Savchynskyy, B., Kappes, J. H., and Schnörr, C., “Partial Optimality by Pruning for MAP-inference with General Graphical Models”, in IEEE Conference on Computer Vision and Pattern Recognition 2014, 2014.
A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections”, Fundamenta Informaticae, vol. 135, p. 73--102, 2014.PDF icon Technical Report (2.24 MB)
A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “Phase Transitions and Cosparse Tomographic Recovery of Compound Solid Bodies from Few Projections”, Fundamenta Informaticae, vol. 135, pp. 73–102, 2014.
F. Besse, Rother, C., Fitzgibbon, A., and Kautz, J., “PMBP: PatchMatch Belief Propagation for correspondence field estimation”, International Journal of Computer Vision, vol. 110, pp. 2–13, 2014.
F. Besse, Rother, C., Fitzgibbon, A., and Kautz, J., “PMBP: PatchMatch Belief Propagation for correspondence field estimation”, International Journal of Computer Vision, vol. 110, pp. 2–13, 2014.
F. Besse, Rother, C., Fitzgibbon, A., and Kautz, J., “PMBP: PatchMatch Belief Propagation for correspondence field estimation”, International Journal of Computer Vision, vol. 110, pp. 2–13, 2014.
F. Rathke, Schmidt, S., and Schnörr, C., “Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization”, Med. Image Anal., vol. 18, pp. 781–794, 2014.
F. Rathke, Schmidt, S., and Schnörr, C., “Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization”, Medical Image Analysis, vol. 18, pp. 781-794, 2014.PDF icon Technical Report (4.07 MB)
F. Rathke, Schmidt, S., and Schnörr, C., “Probabilistic Intra-Retinal Layer Segmentation in 3-D OCT Images Using Global Shape Regularization”, Medical Image Analysis, vol. 18, pp. 781-794, 2014.

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