Publications
2017
Brachmann, E, Krull, A, Nowozin, S, Shotton, J, Michel, F, Gumhold, S and Rother, C (2017).
DSAC - Differentiable RANSAC for camera localization.
Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.
2017-Janua 2492–2500.
http://arxiv.org/abs/1611.05705 Michel, F, Kirillov, A, Brachmann, E, Krull, A, Gumhold, S, Savchynskyy, B and Rother, C (2017).
Global hypothesis generation for 6D object pose estimation.
Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.
2017-Janua 115–124.
http://arxiv.org/abs/1612.02287 Kirillov, A, Levinkov, E, Andres, B, Savchynskyy, B and Rother, C (2017).
InstanceCut: From edges to instances with MultiCut.
Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.
2017-Janua 7322–7331
Levinkov, E, Uhrig, J, Tang, S, Omran, M, Insafutdinov, E, Kirillov, A, Rother, C, Brox, T, Schiele, B and Andres, B (2017).
Joint graph decomposition & node labeling: Problem, algorithms, applications.
Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.
2017-Janua 1904–1912
Kirillov, A, Schlesinger, D, Zheng, S, Savchynskyy, B, Torr, P H S and Rother, C (2017).
Joint training of generic CNN-CRF models with stochastic optimization.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
10112 LNCS 221–236.
http://host.robots.ox.ac.uk:8080/leaderboard Kruse, J, Rother, C and Schmidt, U (2017).
Learning to Push the Limits of Efficient FFT-Based Image Deconvolution.
Proceedings of the IEEE International Conference on Computer Vision.
2017-Octob 4596–4604
Krull, A, Brachmann, E, Nowozin, S, Michel, F, Shotton, J and Rother, C (2017).
PoseAgent: Budget-constrained 6D object pose estimation via reinforcement learning.
Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.
2017-Janua 2566–2574.
http://arxiv.org/abs/1612.03779 Hullin, M, Klein, R, Schultz, T, Yao, A, Li, W, Hosseini Jafari, O and Rother, C (2017).
Semantic-Aware Image Smoothing.
Vision, Modeling, and Visualization.
https://hci.iwr.uni-heidelberg.de/vislearn/wp-content/uploads/2014/08/paper1024_CRC.pdf 2016
Mustikovela, S Karthik, Yang, M Ying and Rother, C (2016).
Can ground truth label propagation from video help semantic segmentation?.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
9915 LNCS 804–820
Royer, L A, Richmond, D L, Rother, C, Andres, B and Kainmueller, D (2016).
Convexity shape constraints for image segmentation.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
2016-Decem 402–410.
http://arxiv.org/abs/1509.02122 Mund, J, Michel, F, Dieke-Meier, F, Fricke, H, Meyer, L and Rother, C (2016).
Introducing LiDAR Point Cloud-based Object Classification for Safer Apron Operations.
International Symposium on Enhanced Solutions for Aircraft and Vehicle Surveillance Applications.
https://goo.gl/28Yoqh Pinggera, P, Ramos, S, Gehrig, S, Franke, U, Rother, C and Mester, R (2016).
Lost and found: Detecting small road hazards for self-driving vehicles.
IEEE International Conference on Intelligent Robots and Systems.
2016-Novem 1099–1106.
http://www.6d-vision.com/lostandfounddataset Sellent, A, Rother, C and Roth, S (2016).
Stereo video deblurring.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
9906 LNCS 558–575
Brachmann, E, Michel, F, Krull, A, Yang, M Ying, Gumhold, S and Rother, C (2016).
Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
2016-Decem 3364–3372
Brachmann, E, Michel, F, Krull, A, Yang, M Ying, Gumhold, S and Rother, C (2016).
Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
2016-Decem 3364–3372
2015
Kappes, J H, 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 (2015).
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
International Journal of Computer Vision.
115 155–184.
http://hci.iwr.uni-heidelberg.de/opengm2/ Kappes, J H, 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 (2015).
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
Int.~J.~Comp.~Vision Technical Report (5.12 MB) Kappes, J H, 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 (2015).
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
International Journal of Computer Vision. 1-30
Technical Report (1.5 MB) Kappes, J H, 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 (2015).
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
International Journal of Computer Vision.
115 155–184
Kappes, J H, 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 (2015).
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
International Journal of Computer Vision.
115 155–184
Abu Alhaija, H, Sellent, A, Kondermann, D and Rother, C (2015).
Graphflow—6D large displacement scene flow via graph matching.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
9358 285–296
Kirillov, A, Savchynskyy, B, Schlesinger, D, Vetrov, D and Rother, C (2015).
Inferring M-best diverse labelings in a single one.
Proceedings of the IEEE International Conference on Computer Vision.
2015 Inter 1814–1822
Krull, A, Brachmann, E, Michel, F, Yang, M Ying, Gumhold, S and Rother, C (2015).
Learning analysis-by-synthesis for 6d pose estimation in RGB-D images.
Proceedings of the IEEE International Conference on Computer Vision.
2015 Inter 954–962
Zheng, S, Prisacariu, V Adrian, Averkiou, M, Cheng, M Ming, Mitra, N J, Shotton, J, Torr, P H S and Rother, C (2015).
Object proposals estimation in depth image using compact 3D shape manifolds.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
9358 196–208
Mitra, N J, Stam, J, Xu, K, Cheng, M - M, Prisacariu, V Adrian, Zheng, S, Torr, P H S and Rother, C (2015).
Pacific Graphics 2015 DenseCut: Densely Connected CRFs for Realtime GrabCut.
34.
http://mftp.mmcheng.net/Papers/DenseCut.pdf Mund, J, Zouhar, A, Meyer, L, Fricke, H and Rother, C (2015).
Performance evaluation of LiDAR point clouds towards automated FOD detection on airport aprons.
Proceedings of ATACCS 2015 - 5th International Conference on Application and Theory of Automation in Command and Control Systems. 85–94
Mund, J, Zouhar, A, Meyer, L, Fricke, H and Rother, C (2015).
Performance evaluation of LiDAR point clouds towards automated FOD detection on airport aprons.
Proceedings of ATACCS 2015 - 5th International Conference on Application and Theory of Automation in Command and Control Systems. 85–94
Pages