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2020

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 (9.95 MB)

A. Bhowmik, Gumhold, S., Rother, C., and Brachmann, E., “Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task”, in CVPR 2020 (oral), 2020.

PDF (2.74 MB)

2019

E. Brachmann and Rother, C., “Expert sample consensus applied to camera re-localization”, in Proceedings of the IEEE International Conference on Computer Vision, 2019, vol. 2019-Octob, pp. 7524–7533.

O. Hosseini Jafari, Mustikovela, S. Karthik, Pertsch, K., Brachmann, E., and Rother, C., “iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11363 LNCS, pp. 477–492.

E. Brachmann and Rother, C., “Neural-guided RANSAC: Learning where to sample model hypotheses”, in Proceedings of the IEEE International Conference on Computer Vision, 2019, vol. 2019-Octob, pp. 4321–4330.

PDF (8.02 MB)

A. Bhowmik, Gumhold, S., Rother, C., and Brachmann, E., “Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task”, 2019.

2018

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.

E. Brachmann and Rother, C., “Learning Less is More - 6D Camera Localization via 3D Surface Regression”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2018, pp. 4654–4662.

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. 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.

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

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.

F. Michel, Krull, A., Brachmann, E., Yang, M. Ying, Gumhold, S., and Rother, C., “Pose Estimation of Kinematic Chain Instances via Object Coordinate Regression”, 2015, pp. 181.1–181.11.