HCI Logo
Heidelberg University Logo
IWR Logo

Publications

Export 185 results:
Author Title [ Type(Asc)] Year
Filters: Author is Carsten Rother  [Clear All Filters]
Journal Article
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”, 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”, 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.
R. Szeliski, Zabih, R., Scharstein, D., Veksler, O., Kolmogorov, V., Agarwala, A., Tappen, M., and Rother, C., “A comparative study of energy minimization methods for Markov random fields with smoothness-based priors”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, pp. 1068–1080, 2008.
R. Szeliski, Zabih, R., Scharstein, D., Veksler, O., Kolmogorov, V., Agarwala, A., Tappen, M., and Rother, C., “A comparative study of energy minimization methods for Markov random fields with smoothness-based priors”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, pp. 1068–1080, 2008.
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.
C. Kamann and Rother, C., “Benchmarking the Robustness of Semantic Segmentation Models”, 2019.
H. Abu Alhaija, Mustikovela, S. K., Mescheder, A., Geiger, C., and Rother, C., “Augmented Reality Meets Computer Vision Efficient Data Generation for Urban Driving Scenes”, IJCV, pp. 1-12, 2018.PDF icon Technical Report (3.83 MB)
H. Abu Alhaija, Mustikovela, S. Karthik, Mescheder, L., Geiger, A., and Rother, C., “Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes”, International Journal of Computer Vision, vol. 126, pp. 961–972, 2018.
H. Abu Alhaija, Mustikovela, S. Karthik, Mescheder, L., Geiger, A., and Rother, C., “Augmented Reality Meets Computer Vision”, International Journal of Computer Vision, vol. In press, pp. 1–13, 2018.
In Collection
D. Richmond, Kainmueller, D., Glocker, B., Rother, C., and Myers, G., “Uncertainty-driven forest predictors for vertebra localization and segmentation”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9349. pp. 653–660, 2015.
Conference Proceedings
H. Schilling, Diebold, M., Rother, C., and Jähne, B., “Trust your Model: Light Field Depth Estimation with inline Occlusion Handling”, CVPR. Proceedings. 2018.PDF icon Technical Report (5.46 MB)
S. Haller, Prakash, M., Hutschenreiter, L., Pietzsch, T., Rother, C., Jug, F., Swoboda, P., and Savchynskyy, B., “A Primal-Dual Solver for Large-Scale Tracking-by-Assignment”, AISTATS 2020. 2020.PDF icon PDF (1.04 MB)
O. Hosseini Jafari, Mustikovela, S. K., Pertsch, K., Brachmann, E., and Rother, C., “iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects”, ACCV. Proceedings, in press. 2018.PDF icon Technical Report (3.28 MB)
H. Abu Alhaija, Mustikovela, S. K., Geiger, A., and Rother, C., “Geometric Image Synthesis”, ACCV. Proceedings, in press. 2018.PDF icon Technical Report (1.83 MB)
Conference Paper
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.
M. Hoai Nguyen, Torresani, L., De La Torre, F., and Rother, C., “Weakly supervised discriminative localization and classification: A joint learning process”, in Proceedings of the IEEE International Conference on Computer Vision, 2009, pp. 1925–1932.
M. Hoai Nguyen, Torresani, L., De La Torre, F., and Rother, C., “Weakly supervised discriminative localization and classification: A joint learning process”, in Proceedings of the IEEE International Conference on Computer Vision, 2009, pp. 1925–1932.
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.
D. S. Kirk, Sellen, A. J., Rother, C., and Wood, K. R., “Understanding photowork”, in Conference on Human Factors in Computing Systems - Proceedings, 2006, vol. 2, pp. 761–770.
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.
H. Schilling, Diebold, M., Rother, C., and Jähne, B., “Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2018, pp. 4530–4538.
B. Glocker, T. Heibel, H., Navab, N., Kohli, P., and Rother, C., “TriangleFlow: Optical flow with triangulation-based higher-order likelihoods”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6313 LNCS, pp. 272–285.
J. Shotton, Winn, J., Rother, C., and Criminisi, A., “TextonBoost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2006, vol. 3951 LNCS, pp. 1–15.
S. Tourani, Shekhovtsov, A., Rother, C., and Savchynskyy, B., “Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization”, in AISTATS 2020, 2020.PDF icon PDF (2.58 MB)
M. Bleyer, Rother, C., and Kohli, P., “Surface stereo with soft segmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 1570–1577.
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.
M. Bleyer, Gelautz, M., Rother, C., and Rhemann, C., “A stereo approach that handles the matting problem via imagewarping”, in 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009, 2009, vol. 2009 IEEE, pp. 501–508.
M. Hornáček, Fitzgibbon, A., and Rother, C., “SphereFlow: 6 DoF scene flow from RGB-D pairs”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2014, pp. 3526–3533.
C. Rhemann, Rother, C., Kohli, P., and Gelautz, M., “A spatially varying PSF-based prior for alpha matting”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 2149–2156.
A. Zouhar, Rother, C., and Fuchs, S., “Semantic 3-D labeling of ear implants using a global parametric transition prior”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9350, pp. 177–184.
A. Mansfield, Gehler, P., Van Gool, L., and Rother, C., “Scene carving: Scene consistent image retargeting”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6311 LNCS, pp. 143–156.

Pages