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2017
E. Brachmann, Krull, A., Nowozin, S., Shotton, J., Michel, F., Gumhold, S., and Rother, C., “DSAC - Differentiable RANSAC for camera localization”, in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017, vol. 2017-Janua, pp. 2492–2500.
F. Michel, Kirillov, A., Brachmann, E., Krull, A., Gumhold, S., Savchynskyy, B., and Rother, C., “Global hypothesis generation for 6D object pose estimation”, in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017, vol. 2017-Janua, pp. 115–124.
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.
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.
A. Kirillov, Schlesinger, D., Zheng, S., Savchynskyy, B., Torr, P. H. S., and Rother, C., “Joint training of generic CNN-CRF models with stochastic optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10112 LNCS, pp. 221–236.
J. Kruse, Rother, C., and Schmidt, U., “Learning to Push the Limits of Efficient FFT-Based Image Deconvolution”, in Proceedings of the IEEE International Conference on Computer Vision, 2017, vol. 2017-Octob, pp. 4596–4604.
J. Kruse, Rother, C., Schmidt, U., and Dresden, T. U., “Learning to Push the Limits of Efficient FFT-based Image Deconvolution - Supplemental Material”, 2017.
A. Krull, Brachmann, E., Nowozin, S., Michel, F., Shotton, J., and Rother, C., “PoseAgent: Budget-constrained 6D object pose estimation via reinforcement learning”, in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017, vol. 2017-Janua, pp. 2566–2574.
D. Massiceti, Krull, A., Brachmann, E., Rother, C., and Torr, P. H. S., “Random Forests versus Neural Networks − What's best for camera location”. 2017.
M. Hullin, Klein, R., Schultz, T., Yao, A., Li, W., Hosseini Jafari, O., and Rother, C., “Semantic-Aware Image Smoothing”, Vision, Modeling, and Visualization, 2017.
2016
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.
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. Mund, Michel, F., Dieke-Meier, F., Fricke, H., Meyer, L., and Rother, C., “Introducing LiDAR Point Cloud-based Object Classification for Safer Apron Operations”, in International Symposium on Enhanced Solutions for Aircraft and Vehicle Surveillance Applications, 2016.
P. Pinggera, Ramos, S., Gehrig, S., Franke, U., Rother, C., and Mester, R., “Lost and found: Detecting small road hazards for self-driving vehicles”, in IEEE International Conference on Intelligent Robots and Systems, 2016, vol. 2016-Novem, pp. 1099–1106.
D. L. Richmond, Kainmueller, D., Yang, M. Y., Myers, E. W., and Rother, C., “Mapping auto-context decision forests to deep convnets for semantic segmentation”, in British Machine Vision Conference 2016, BMVC 2016, 2016, vol. 2016-Septe, pp. 144.1–144.12.
D. L. Richmond, Kainmueller, D., Yang, M. Y., Myers, E. W., and Rother, C., “Mapping auto-context decision forests to deep convnets for semantic segmentation”, in British Machine Vision Conference 2016, BMVC 2016, 2016, vol. 2016-Septe, pp. 144.1–144.12.
D. L. Richmond, Kainmueller, D., Yang, M. Y., Myers, E. W., and Rother, C., “Mapping auto-context decision forests to deep convnets for semantic segmentation”, in British Machine Vision Conference 2016, BMVC 2016, 2016, vol. 2016-Septe, pp. 144.1–144.12.
A. Sellent, Rother, C., and Roth, S., “Stereo video deblurring”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, vol. 9906 LNCS, pp. 558–575.
A. Sellent, Rother, C., and Roth, S., “Stereo Video Deblurring-Supplemental Material”, 2016.
E. Brachmann, Michel, F., Krull, A., Yang, M. Ying, Gumhold, S., and Rother, C., “Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016, vol. 2016-Decem, pp. 3364–3372.
E. Brachmann, Michel, F., Krull, A., Yang, M. Ying, Gumhold, S., and Rother, C., “Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016, vol. 2016-Decem, pp. 3364–3372.
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)
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.
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.
A. Kirillov, Savchynskyy, B., Schlesinger, D., Vetrov, D., and Rother, C., “Inferring M-best diverse labelings in a single one”, in Proceedings of the IEEE International Conference on Computer Vision, 2015, vol. 2015 Inter, pp. 1814–1822.
K. Schelten, Nowozin, S., Jancsary, J., Rother, C., and Roth, S., “Interleaved regression tree field cascades for blind image deconvolution”, in Proceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015, 2015, pp. 494–501.
A. Krull, Brachmann, E., Michel, F., Yang, M. Ying, Gumhold, S., and Rother, C., “Learning analysis-by-synthesis for 6d pose estimation in RGB-D images”, in Proceedings of the IEEE International Conference on Computer Vision, 2015, vol. 2015 Inter, pp. 954–962.
A. Kirillov, Schlesinger, D., Vetrov, D., Rother, C., and Savchynskyy, B., “M-best-diverse labelings for submodular energies and beyond”, in Advances in Neural Information Processing Systems, 2015, vol. 2015-Janua, pp. 613–621.
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.
N. J. Mitra, Stam, J., Xu, K., Cheng, M. - M., Prisacariu, V. Adrian, Zheng, S., Torr, P. H. S., and Rother, C., “Pacific Graphics 2015 DenseCut: Densely Connected CRFs for Realtime GrabCut”, vol. 34, 2015.
J. Mund, Zouhar, A., Meyer, L., Fricke, H., and Rother, C., “Performance evaluation of LiDAR point clouds towards automated FOD detection on airport aprons”, in Proceedings of ATACCS 2015 - 5th International Conference on Application and Theory of Automation in Command and Control Systems, 2015, pp. 85–94.
J. Mund, Zouhar, A., Meyer, L., Fricke, H., and Rother, C., “Performance evaluation of LiDAR point clouds towards automated FOD detection on airport aprons”, in Proceedings of ATACCS 2015 - 5th International Conference on Application and Theory of Automation in Command and Control Systems, 2015, pp. 85–94.

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