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2014
A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography”, in Discrete Geometry for Computer Imagery (DGCI) 2014, 2014, pp. 262–274.
A. Denitiu, Petra, S., Schnörr, C., and Schnörr, C., “An Entropic Perturbation Approach to TV-Minimization for Limited-Data Tomography”, in Discrete Geometry for Computer Imagery (DGCI) 2014, 2014, pp. 262–274.
M. Kandemir, Rubio, J. C., Schmidt, U., Wojek, C., Welbl, J., Ommer, B., and Hamprecht, F. A., “Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures”, in Medical Image Computing and Computer-Assisted Intervention, 2014, p. 154--161.PDF icon Technical Report (2 MB)
M. Kandemir, Rubio, J. C., Schmidt, U., Welbl, J., Ommer, B., and Hamprecht, F. A., “Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures”, in MICCAI. Proceedings, 2014, pp. 154-161.PDF icon Paper (2 MB)
M. Knorr, Esparza, J., Niehsen, W., and Stiller, C., “Extrinsic calibration of a fisheye multi-camera setup using overlapping fields of view”, in Intelligent Vehicles Symposium Proceedings, 2014, p. 1276--1281.
B. Schmitzer and Schnörr, C., “Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes”. 2014.PDF icon Technical Report (2.9 MB)
B. Schmitzer and Schnörr, C., “Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes”. 2014.PDF icon Technical Report (2.9 MB)
B. Schmitzer and Schnörr, C., “Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes”. 2014.
B. Schmitzer and Schnörr, C., “Globally Optimal Joint Image Segmentation and Shape Matching based on Wasserstein Modes”. 2014.
R. Lindner, Lou, X., Reinstein, J., Shoeman, R. L., Hamprecht, F. A., and Winkler, A., “Hexicon 2: Automated Processing of Hydrogen-Deuterium Exchange Mass Spectrometry Data with Improved Deuteration Distribution Estimation”, Journal of The American Society for Mass Spectrometry, vol. 25, pp. 1018-1028, 2014.PDF icon Technical Report (2.1 MB)
C. N. Straehle, “Interactive Segmentation, Uncertainty and Learning”. University of Heidelberg, 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)
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.
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.
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)
F. Becker, Petra, S., and Schnörr, C., “Optical Flow”, Handbook of Mathematical Methods in Imaging. Springer, 2014.
F. Becker, Petra, S., and Schnörr, C., “Optical Flow”, Handbook of Mathematical Methods in Imaging. Springer, 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 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 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.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.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.
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.
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, 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.
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. 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”, 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.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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