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Conference Paper
D. Hoiem, Rother, C., and Winn, J., “3D LayoutCRF for multi-view object class recognition and segmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2007.
A. Shesh, Criminisi, A., Rother, C., and Smyth, G., “3D-aware image editing for out of bounds photography”, in Proceedings - Graphics Interface, 2009, pp. 47–54.
D. Kainmueller, Jug, F., Rother, C., and Myers, G., “Active graph matching for automatic joint segmentation and annotation of C. elegans”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, vol. 8673 LNCS, pp. 81–88.
M. Sindeev, Konushin, A., and Rother, C., “Alpha-flow for video matting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, vol. 7726 LNCS, pp. 438–452.
O. Hosseini Jafari, Groth, O., Kirillov, A., Yang, M. Ying, and Rother, C., “Analyzing modular CNN architectures for joint depth prediction and semantic segmentation”, in Proceedings - IEEE International Conference on Robotics and Automation, 2017, pp. 4620–4627.
V. Kolmogorov, Boykov, Y., and Rother, C., “Applications of parametric maxflow in computer vision”, in Proceedings of the IEEE International Conference on Computer Vision, 2007.
V. Kolmogorov, Boykov, Y., and Rother, C., “Applications of parametric maxflow in computer vision”, in Proceedings of the IEEE International Conference on Computer Vision, 2007.
H. Abu Alhaija, Mustikovela, S. Karthik, Mescheder, L., Geiger, A., and Rother, C., “Augmented reality meets deep learning for car instance segmentation in urban scenes”, in British Machine Vision Conference 2017, BMVC 2017, 2017.
P. Vincent Gehler, Rother, C., Blake, A., Minka, T., and Sharp, T., “Bayesian color constancy revisited”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.
V. Kolmogorov, Criminisi, A., Blake, A., Cross, G., and Rother, C., “Bi-layer segmentation of binocular stereo video”, in Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, 2005, vol. II, pp. 407–414.
T. Hodaň, Michel, F., Brachmann, E., Kehl, W., Buch, A. Glent, Kraft, D., Drost, B., Vidal, J., Ihrke, S., Zabulis, X., Sahin, C., Manhardt, F., Tombari, F., Kim, T. Kyun, Matas, J., and Rother, C., “BOP: Benchmark for 6D object pose estimation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, vol. 11214 LNCS, pp. 19–35.
A. Behl, Hosseini Jafari, O., Mustikovela, S. Karthik, Abu Alhaija, H., Rother, C., and Geiger, A., “Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?”, in Proceedings of the IEEE International Conference on Computer Vision, 2017, vol. 2017-Octob, pp. 2593–2602.
A. Behl, Hosseini Jafari, O., Mustikovela, S. Karthik, Abu Alhaija, H., Rother, C., and Geiger, A., “Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?”, in Proceedings of the IEEE International Conference on Computer Vision, 2017, vol. 2017-Octob, pp. 2593–2602.
S. Karthik Mustikovela, Yang, M. Ying, and Rother, C., “Can ground truth label propagation from video help semantic segmentation?”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, vol. 9915 LNCS, pp. 804–820.
R. Mackowiak, Lenz, P., Ghori, O., Diego, F., Lange, O., and Rother, C., “CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation”, in British Machine Vision Conference 2018, BMVC 2018, 2019.
A. Kannan, Winn, J., and Rother, C., “Clustering appearance and shape by learning jigsaws”, in Advances in Neural Information Processing Systems, 2007, pp. 657–664.
A. Kannan, Winn, J., and Rother, C., “Clustering appearance and shape by learning jigsaws”, in Advances in Neural Information Processing Systems, 2007, pp. 657–664.
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Sungwoong, K., Kausler, B. X., Lellmann, J., Komodakis, N., and Rother, C., “A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems”, in CVPR 2013. Proceedings, 2013.PDF icon Technical Report (1.35 MB)
J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Lellmann, J., Komodakis, N., and Rother, C., “A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problem”, in CVPR, 2013.PDF icon Technical Report (1.35 MB)
V. Kolmogorov and Rother, C., “Comparison of energy minimization algorithms for highly connected graphs”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2006, vol. 3952 LNCS, pp. 1–15.
V. Kolmogorov and Rother, C., “Comparison of energy minimization algorithms for highly connected graphs”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2006, vol. 3952 LNCS, pp. 1–15.
F. Kluger, Brachmann, E., Ackermann, H., Rother, C., Yang, M. Ying, and Rosenhahn, B., “CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus”, in CVPR 2020, 2020.PDF icon PDF (9.95 MB)
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.
C. Rother, Kolmogorov, V., Minka, T., and Blake, A., “Cosegmentation of image pairs by histogram matching - Incorporating a global constraint into MRFs”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2006, vol. 1, pp. 994–1000.
S. Vicente, Kolmogorov, V., and Rother, C., “Cosegmentation revisited: Models and optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6312 LNCS, pp. 465–479.
D. Schlesinger, Jug, F., Myers, G., Rother, C., and Kainmueller, D., “Crowd sourcing image segmentation with iaSTAPLE”, in Proceedings - International Symposium on Biomedical Imaging, 2017, pp. 401–405.
A. Shekhovtsov, Kohli, P., and Rother, C., “Curvature prior for MRF-based segmentation and shape inpainting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7476 LNCS, pp. 41–51.
A. Shekhovtsov, Kohli, P., and Rother, C., “Curvature prior for MRF-based segmentation and shape inpainting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7476 LNCS, pp. 41–51.
A. Shekhovtsov, Kohli, P., and Rother, C., “Curvature prior for MRF-based segmentation and shape inpainting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7476 LNCS, pp. 41–51.
S. Nowozin, Rother, C., Bagon, S., Sharp, T., Yao, B., and Kohli, P., “Decision tree fields”, in Proceedings of the IEEE International Conference on Computer Vision, 2011, pp. 1668–1675.
W. Li, Hosseini Jafari, O., and Rother, C., “Deep Object Co-segmentation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11363 LNCS, pp. 638–653.
S. Zheng, Cheng, M. Ming, Warrell, J., Sturgess, P., Vineet, V., Rother, C., and Torr, P. H. S., “Dense semantic image segmentation with objects and attributes”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2014, pp. 3214–3221.
M. Hornáček, Rhemann, C., Gelautz, M., and Rother, C., “Depth super resolution by rigid body self-similarity in 3D”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2013, pp. 1123–1130.
S. Ramos, Gehrig, S., Pinggera, P., Franke, U., and Rother, C., “Detecting unexpected obstacles for self-driving cars: Fusing deep learning and geometric modeling”, in IEEE Intelligent Vehicles Symposium, Proceedings, 2017, pp. 1025–1032.
C. Rother, Kumar, S., Kolmogorov, V., and Blake, A., “Digital tapestry [automatic image synthesis]”, in Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, 2005, vol. 1, pp. 589–596.

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