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A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

S

B. Andres, Hamprecht, F. A., and Garbe, C. S., “Selection of Local Optical Flow Models by Means of Residual Analysis”, in Pattern Recognition, 2007, vol. 4713, pp. 72-81.

Technical Report (229.64 KB)

B. Andres, Garbe, C. S., Schnörr, C., and Jähne, B., “Selection of local optical flow models by means of residual analysis”, in Proceedings of the 29th DAGM Symposium on Pattern Recognition, 2007, p. 72--81.

B. Andres, Köthe, U., Helmstaedter, M., Denk, W., and Hamprecht, F. A., “Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification”, in Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings, 2008, vol. 5096, pp. 142-152.

Technical Report (1.21 MB)

R

B. Andres, Köthe, U., Kröger, T., and Hamprecht, F. A., “Runtime-Flexible Multi-dimensional Views and Arrays for C++98 and C++0x”, ArXiv e-prints, 2010.

Technical Report (415.54 KB)

Q

B. Andres, Köthe, U., Bonea, A., Nadler, B., and Hamprecht, F. A., “Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times”, in Pattern Recognition. 31st DAGM Symposium, Jena, Germany, September 9-11, 2009. Proceedings, 2009, vol. 5748, pp. 502-511.

Technical Report (3.08 MB)

P

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Probabilistic Image Segmentation with Closedness Constraints”, in Proceedings of ICCV, 2011.

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Probabilistic Image Segmentation with Closedness Constraints”, in ICCV, Proceedings, 2011, pp. 2611 - 2618.

Technical Report (8.18 MB)

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “Probabilistic Image Segmentation with Closedness Constraints”, in Proceedings of ICCV, 2011.

Technical Report (2.95 MB)

O

B. Andres, Beier, T., and Kappes, J. H., “OpenGM: A C++ Library for Discrete Graphical Models”, ArXiv e-prints, 2012.

N

C. S. Garbe, Krajsek, K., Pavlov, P., Andres, B., Mühlich, M., Stuke, I., Mota, C., Böhme, M., Haker, M., Schucher, T., Scharr, H., Aach, T., and Barth, E., “Nonlinear analysis of multi-dimensional signals: local adaptive estimation of complex motion and orientation patterns”, Mathematical Methods in Time Series Analysis and Digital Image Processing. Springer, pp. 231-288, 2008.

C. S. Garbe, Krajsek, K., Pavlov, P., Andres, B., Mühlich, M., Stuke, I., Mota, C., Böhme, M., Haker, M., Schuchert, T., Scharr, H., Aach, T., and Barth, E., “Nonlinear Analysis of Multi-Dimensional Signals”, Mathematical Methods in Signal Processing and Digital Image Analysis. Springer, pp. 231-288, 2008.

Technical Report (7.11 MB)

M

B. Andres, “Model Selection in Optical Flow-Based Motion Estimation by Means of Residual Analysis”, University of Heidelberg, 2007.

B. Andres, “Model Selection in Optical Flow-Based Motion Estimation by Means of Residual Analysis”, University of Heidelberg, 2007.

L

B. Andres, Kappes, J. H., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search”, ArXiv e-prints, 2010.

Technical Report (625.06 KB)

B. Andres, Kappes, J. Hendrik, Beier, T., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models”, in ECCV 2012, 2012.

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models”, in ECCV 2012, 2012.

Technical Report (532.64 KB)

B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., “The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models”, in Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}, 2012.

Technical Report (446.28 KB)

J

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.

I

A. Kirillov, Levinkov, E., Andres, B., Savchynskyy, B., and Rother, C., “InstanceCut: From edges to instances with MultiCut”, in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017, vol. 2017-Janua, pp. 7322–7331.

H

B. Andres, Köthe, U., Kröger, T., and Hamprecht, F. A., “How to Extract the Geometry and Topology from Very Large 3D Segmentations”, ArXiv e-prints, 2010.

Technical Report (1.44 MB)

G

J. H. Kappes, Speth, M., Andres, B., Reinelt, G., and Schnörr, C., “Globally Optimal Image Partitioning by Multicuts”, in EMMCVPR, 2011.

Technical Report (7.47 MB)

J. Hendrik Kappes, Speth, M., Andres, B., Reinelt, G., and Schnörr, C., “Globally Optimal Image Partitioning by Multicuts”, in EMMCVPR, 2011.

J. H. Kappes, Speth, M., Andres, B., Reinelt, G., and Schnörr, C., “Globally Optimal Image Partitioning by Multicuts”, in EMMCVPR, 2011, pp. 31-44.

Technical Report (7.3 MB)

B. Andres, Kröger, T., Briggmann, K. L., Denk, W., Norogod, N., Knott, G. W., Köthe, U., and Hamprecht, F. A., “Globally Optimal Closed-Surface Segmentation for Connectomics”, in ECCV 2012. Proceedings, Part 3, 2012, pp. 778-791.

Technical Report (2.72 MB)

U. Köthe, Andres, B., Kröger, T., and Hamprecht, F. A., “Geometric Analysis of 3D Electron Microscopy Data”, in Proceedings of Workshop on Discrete Geometry and Mathematical Morphology (WADGMM), 2010, pp. 22-26.

Technical Report (1.43 MB)

E

B. Andres, Kondermann, C., Kondermann, D., Hamprecht, F. A., and Garbe, C. S., “On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation”, in IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, 2008, p. 1--6.

B. Andres, Kondermann, C., Kondermann, D., Köthe, U., Hamprecht, F. A., and Garbe, C. S., “On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation”, Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pp. 1-6, 2008.

Technical Report (1.58 MB)

B. Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., “An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM”, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010, pp. 353-362.

B. Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., “An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM”, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010.

Technical Report (218.43 KB)

T. Beier, Andres, B., Köthe, U., and Hamprecht, F. A., “An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem”, ECCV. Proceedings, vol. LNCS 9906. Springer, pp. 715-730, 2016.

Technical Report (4.89 MB)

J. Funke, Andres, B., Hamprecht, F. A., Cardona, A., and Cook, M., “Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data”, CVPR 2012. Proceedings, pp. 1004-1011, 2012.

Technical Report (1.64 MB)

D

B. X. Kausler, Schiegg, M., Andres, B., Lindner, M., Köthe, U., Leitte, H., Wittbrodt, J., Hufnagel, L., and Hamprecht, F. A., “A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness”, in ECCV 2012. Proceedings, 2012, vol. 7574, pp. 144-157.

Technical Report (809.07 KB)

C

L. A. Royer, Richmond, D. L., Rother, C., Andres, B., and Kainmueller, D., “Convexity shape constraints for image segmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016, vol. 2016-Decem, pp. 402–410.

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, CoRR, vol. abs/1404.0533, 2014.

Technical Report (3.32 MB)

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.

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