Publications


Books

2018

  • H. Abu Alhaija, S.K. Mustikovela,L. Mescheder, A. Geiger, C. Rother, “Augmented Reality Meets Computer Vision
    Efficient Data Generation for Urban Driving Scenes” , IJCV(2018) [link] [pdf]
  • E. Brachmann, C. Rother, “Learning Less is More – 6D Camera Localization via 3D Surface Regression”, CVPR 2018. [pdf][project page]
  • H. Schilling, M. Diebold, C. Rother, B. Jähne, “Trust your Model: Light Field Depth Estimation with inline Occlusion Handling”, CVPR 2018. [pdf]
  • S. Haller, P. Swoboda and B. Savchynskyy. Exact MAP-Inference by Confining Combinatorial Search with LP Relaxation. Accepted to AAAI 2018. [pdf]

2017

  • A. Arnab, S. Zheng, S. Jayasumana, B. Romera-Paredes, M. Larsson, A. Kirillov, B. Savchynskyy, C. Rother, F. Kahl, and P.H.S. Torr. Conditional Random Fields meet Deep Neural Networks for Semantic Segmentation. IEEE Signal Processing Magazine Special Issue in Deep Learning for Visual Understanding White Paper. 2017 (accepted).
  • H. Abu Alhaija , S. K. Mustikovela, L. Mescheder, A. Geiger, C. Rother, “Augmented Reality Meets Deep Learning for Car Instance Segmentation in Urban Scenes”, BMVC 2017. [pdf][extended Arxiv pdf]
  • W. Li, O. Hosseini Jafari, C. Rother, ”Semantic-Aware Image Smoothing”, VMV 2017. [pdf]
  • J. Kruse, C. Rother, U. Schmidt, “Learning to Push the Limits of Efficient FFT-based Image Deconvolution”, ICCV 2017. [pdf][supp]
  • A. Behl, O. Hosseini Jafari, S. K. Mustikovela, H. Abu Alhaija, C. Rother, A. Geiger, “Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?”, ICCV 2017. [pdf][supp]
  • S. Ramos, S. Gehrig, P. Pinggera, U. Franke, C. Rother. “Detecting Unexpected Obstacles for Self-Driving Cars: Fusing Deep Learning and Geometric Modeling.” , Intelligent Vehicles Symposium (IV)(Oral)[pdf]
  • E. Brachmann, A. Krull, S. Nowozin, J. Shotton, F. Michel, S. Gumhold, C. Rother, “DSAC – Differentiable RANSAC for Camera Localization”, CVPR 2017 (oral). [pdf][project page]
  • P. Swoboda, J. Kuske, B. Savchynskyy “A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems”. CVPR 2017. [pdf]
  • P. Swoboda, C. Rother, H. A. Alhaija, D. Kainmueller, B. Savchynskyy “A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching”. CVPR 2017. [pdf]
  • A. Kirillov, E. Levinkov, B. Andres, B. Savchynskyy, C. Rother, “InstanceCut: from Edges to Instances with MultiCut”, CVPR 2017. [pdf]
  • F. Michel, A. Kirillov, E. Brachmann, A. Krull, S. Gumhold, B. Savchynskyy, C. Rother, “Global Hypothesis Generation for 6D Object Pose Estimation”, CVPR 2017. [pdf][project page]
  • E. Levinkov, J. Uhrig, S. Tang, M. Omran, E. Insafutdinov, A. Kirillov, C. Rother, T. Brox, B. Schiele, B. Andres, “Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications”, CVPR 2017. [pdf]
  • A. Krull, E. Brachmann, S. Nowozin, F. Michel, J. Shotton, C. Rother, “PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning”, CVPR 2017. [pdf][project page]
  • Daniela Massiceti, Alexander Krull, Eric Brachmann, Carsten Rother, Philip H.S. Torr, “Random Forests versus Neural Networks − What’s Best for Camera Localization?”, ICRA 2017. [pdf]
  • Dmitrij Schlesinger, Florian Jug, Gene Myers, Carsten Rother, Dagmar Kainmüller, “Crowd Sourcing Image Segmentation with iaSTAPLE”, ISBI 2017. [pdf]
  • O. Hosseini Jafari, O. Groth, A. Kirillov, M. Y. Yang, C. Rother, “Analyzing Modular CNN Architectures for Joint Depth Prediction and Semantic Segmentation”, ICRA 2017. [pdf]

2016

  • S. K. Mustikovela, M. Y. Yang, C.Rother, “Can Ground Truth Label Propagation from Video help Semantic Segmentation?”, Video Segmentation Workshop, ECCV 2016. [pdf]
  • P. Pinggera, S. Ramos, S. Gehrig, U. Franke, C. Rother, R. Mester, “Lost and Found: Detecting Small Road Hazards for Self-Driving Vehicles”, IROS 2016. [pdf]
  • A. Kirillov, A. Shekhovtsov, C. Rother, B. Savchynskyy, “Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization”, NIPS 2016, in press. [preprint]
  • A. Kirillov, D. Schlesinger, S. Zheng, B. Savchynskyy, P.H.S. Torr, C. Rother, “Joint Training of Generic CNN-CRF Models with Stochastic Optimization”, ACCV 2016, in press. [pdf]
  • Kappes, J.H.; Swoboda, P.; Savchynskyy, B.; Hazan, T. and Schnörr, C., “Multicuts and Perturb & MAP for Probabilistic Graph Clustering”, In J. Math. Imag. Vision, in press, 2016. [preprint] [bib]
  • Swoboda, P.; Shekhovtsov, A.; Kappes, J.H.; Schnörr, C. and Savchynskyy, B., “Partial Optimality by Pruning for MAP-Inference with General Graphical Models”, In IEEE Trans. Patt. Anal. Mach. Intell., vol. 38, July 2016, pp. 1370-1382. [preprint] [bib]
  • A. Sellent, C. Rother, S. Roth,”Stereo Video Deblurring”, ECCV 2016. [pdf][supp]
  • D. L. Richmond, D. Kainmueller, M. Y. Yang, E. W. Myers, C. Rother, “Mapping Auto-context Decision Forests to Deep ConvNets for Semantic Segmentation”, BMVC 2016. [pdf] [supplement]
  • L. A. Royer,D. L. Richmond ,C. Rother ,B. Andres and D. Kainmueller “Convexity Shape Constraints for Image Segmentation”, CVPR 2016 [pdf]
  • J. Mund, F. Michel, F. Dieke-Meier, H. Fricke, L. Meyer, C. Rother, “Introducing LiDAR Point Cloud-based Object Classification for Safer Apron Operations”, ESAVS 2016 [pdf].
  • E. Brachmann, F. Michel, A. Krull, M. Y. Yang, S. Gumhold, C. Rother, “Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image”, CVPR 2016.[pdf][supplement][project page]
  • F. Matulic, W. Büschel, M. Y. Yang, S. Ihrke, A. Ramraika, C. Rother, R. Dachselt, “Smart Ubiquitous Projection: Discovering Surfaces for the Projection of Adaptive Content”, Proceedings of the 34th Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, 2016.
  • O. Hosseini Jafari, M. Y. Yang, “Real-Time RGB-D based Template Matching Pedestrian Detection”, ICRA 2016. [pdf]

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

  • Carsten Rother, Analyse initialer Positionsschätzungen bei der Bildfolgenauswertung, DAGM 1999