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Author Title Type [ Year(Desc)]
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2011
S. Vicente, Rother, C., and Kolmogorov, V., “Object cosegmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2011, pp. 2217–2224.
M. Bleyer, Rother, C., Kohli, P., Scharstein, D., and Sinha, S., “Object stereo Joint stereo matching and object segmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2011, pp. 3081–3088.
M. Bleyer, Rhemann, C., and Rother, C., “PatchMatch Stereo - Stereo Matching with Slanted Support Windows”, 2011, pp. 14.1–14.11.
P. Pletscher, Nowozin, S., Kohli, P., and Rother, C., “Putting MAP back on the map”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, vol. 6835 LNCS, pp. 111–121.
P. Pletscher, Nowozin, S., Kohli, P., and Rother, C., “Putting MAP back on the map”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, vol. 6835 LNCS, pp. 111–121.
P. Vincent Gehler, Rother, C., Kiefel, M., Zhang, L., and Schölkopf, B., “Recovering intrinsic images with a global sparsity prior on reflectance”, in Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011, 2011.
C. Rother, “Sparse Higher Order Functions of Discrete Variables–-Representation and Optimization”, research.microsoft.com, vol. 45, 2011.
2012
V. Lempitsky, Blake, A., and Rother, C., “Branch-and-mincut: Global optimization for image segmentation with high-level priors”, Journal of Mathematical Imaging and Vision, vol. 44, pp. 315–329, 2012.
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.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.
J. Jancsary, Nowozin, S., and Rother, C., “Loss-specific training of non-parametric image restoration models: A new state of the art”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7578 LNCS, pp. 112–125.
J. Jancsary, Nowozin, S., and Rother, C., “Loss-specific training of non-parametric image restoration models: A new state of the art”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7578 LNCS, pp. 112–125.
J. Jancsary, Nowozin, S., and Rother, C., “Non-parametric crfs for image labeling”, in NIPS Workshop Modern Nonparametric Methods in Machine Learning, 2012, pp. 1–5.
J. Jancsary, Nowozin, S., Sharp, T., and Rother, C., “Regression Tree Fields An efficient, non-parametric approach to image labeling problems”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2012, pp. 2376–2383.
J. Jancsary, Nowozin, S., Sharp, T., and Rother, C., “Regression Tree Fields An efficient, non-parametric approach to image labeling problems”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2012, pp. 2376–2383.
P. Kohli, Nickisch, H., Rother, C., and Rhemann, C., “User-centric learning and evaluation of interactive segmentation systems”, International Journal of Computer Vision, vol. 100, pp. 261–274, 2012.
A. Mansfield, Gehler, P., Van Gool, L., and Rother, C., “Visibility maps for improving seam carving”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 6554 LNCS, pp. 131–144.
S. Meister, Izadi, S., Kohli, P., Hämmerle, M., Rother, C., and Kondermann, D., “When Can We Use KinectFusion for Ground Truth Acquisition?”, in Workshop on Color-Depth Camera Fusion in Robotics, IEEE International Conference on Intelligent Robots and Systems, 2012.
2013
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.
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)
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.
U. Schmidt, Rother, C., Nowozin, S., Jancsary, J., and Roth, S., “Discriminative Non-blind Deblurring”, 2013.
A. Hosni, Rhemann, C., Bleyer, M., Rother, C., and Gelautz, M., “Fast cost-volume filtering for visual correspondence and beyond”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, pp. 504–511, 2013.
V. Vineet, Rother, C., and Torr, P. H. S., “Higher order priors for joint intrinsic image, objects, and attributes estimation”, in Advances in Neural Information Processing Systems, 2013.
J. Jancsary, Nowozin, S., and Rother, C., “Learning convex QP relaxations for structured prediction”, in 30th International Conference on Machine Learning, ICML 2013, 2013, pp. 1952–1960.
2014
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.
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.
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)
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, Besse, F., Kautz, J., Fitzgibbon, A., and Rother, C., “Highly overparameterized optical flow using PatchMatch belief propagation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, vol. 8691 LNCS, pp. 220–234.
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.

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