Publications

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2016
F. Aström, Petra, S., Schmitzer, B., and Schnörr, C., The Assignment Manifold: A Smooth Model for Image Labeling, in Proc. 2nd Int. Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16; oral presentation; Grenander best paper award), 2016.
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.
F. Aström and Schnörr, C., Double-Opponent Vectorial Total Variation, in Proc. ECCV, 2016.
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.PDF icon Technical Report (4.89 MB)
H. Schilling, Diebold, M., Gutsche, M., Aziz-Ahmad, H., and Jähne, B., A fractal calibration pattern for improved camera calibration, Forum Bildverarbeitung. 2016.
C. Haubold, Ales, J., Wolf, S., and Hamprecht, F. A., A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets, ECCV. Proceedings, vol. LNCS 9911. Springer, pp. 566-582, 2016.PDF icon Technical Report (1.18 MB)
F. Aström and Schnörr, C., A Geometric Approach to Color Image Regularization. 2016.
F. Aström, Petra, S., Schmitzer, B., and Schnörr, C., A Geometric Approach to Image Labeling, in Proc. ECCV, 2016.
D. Kondermann, Nair, R., Honauer, K., Krispin, K., Andrulis, J., Brock, A., Güssefeld, B., Rahimimoghaddam, M., Hofmann, S., Brenner, C., and Jähne, B., The HCI Benchmark Suite: Stereo and Flow Ground Truth With Uncertainties for Urban Autonomous Driving, in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016.
F. Aström, Petra, S., Schmitzer, B., and Schnörr, C., Image Labeling by Assignment. 2016.
2015
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, pp. 1-30, 2015.PDF icon Technical Report (1.5 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.
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.
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.
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, Int.~J.~Comp.~Vision, 2015.PDF icon Technical Report (5.12 MB)
H. Abu Alhaija, Sellent, A., Kondermann, D., and Rother, C., Graphflow—6D large displacement scene flow via graph matching, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9358, pp. 285–296.
S. Zheng, Prisacariu, V. Adrian, Averkiou, M., Cheng, M. Ming, Mitra, N. J., Shotton, J., Torr, P. H. S., and Rother, C., Object proposals estimation in depth image using compact 3D shape manifolds, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9358, pp. 196–208.
B. Antic and Ommer, B., Per-Sample Kernel Adaptation for Visual Recognition and Grouping, in Proceedings of the IEEE International Conference on Computer Vision, 2015.PDF icon Technical Report (1.58 MB)
B. Antic, Büchler, U., Wahl, A. - S., Schwab, M. E., and Ommer, B., Spatiotemporal Parsing of Motor Kinematics for Assessing Stroke Recovery, in Medical Image Computing and Computer-Assisted Intervention, 2015.PDF icon Article (2.24 MB)
B. Antic and Ommer, B., Spatio-temporal Video Parsing for Abnormality Detection, arXiv, vol. abs/1502.06235, 2015.PDF icon Technical Report (4.61 MB)
N. Arnold, Visualisierung des Gasaustauschs an der windbewegten Wasseroberfläche mittels vertikaler Konzentrationsfelder von gelöstem Sauerstoff quer zur Windrichtung, Institut für Umweltphysik, Universität Heidelberg, Germany, 2015.
2014
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.PDF icon 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, CoRR, 2014.
E. Eyjolfsdottir, Branson, S., Burgos-Artizzu, X. P., Hoopfer, E. D., Schor, J., Anderson, D. J., and Perona, P., Detection of social actions in fruit flies, Lecture Notes in Computer Science, vol. 8690, pp. 772–787, 2014.
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)
A. Drory, Haubold, C., Avidan, S., and Hamprecht, F. A., Semi-Global Matching: A Principled Derivation in Terms of Message Passing, in GCPR. Proceedings, 2014, pp. 43-53.PDF icon Technical Report (2.6 MB)
B. Goldlücke, Aubry, M., Kolev, K., and Cremers, D., A super-resolution framework for high-accuracy multiview reconstruction, Int. J. Comp. Vision, vol. 106, p. 172--191, 2014.

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