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H

V. Vineet, Rother, C., and Torr, P. H. S., “Higher order priors for joint intrinsic image, objects, and attributes estimation”, in Advances in Neural Information Processing Systems, 2013.

C. Rhemann, Rother, C., Rav-Acha, A., and Sharp, T., “High resolution matting via interactive trimap segmentation”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.

C. Rhemann, Rother, C., Rav-Acha, A., and Sharp, T., “High resolution matting via interactive trimap segmentation”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.

C. Rhemann, Rother, C., Rav-Acha, A., and Sharp, T., “High resolution matting via interactive trimap segmentation”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.

G

L. Ardizzone, Lüth, C., Kruse, J., Rother, C., and Köthe, U., “Guided Image Generation with Conditional Invertible Neural Networks”, 2019.

L. Ardizzone, Lüth, C., Kruse, J., Rother, C., and Köthe, U., “Guided Image Generation with Conditional Invertible Neural Networks”, 2019.

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.

S. Vicente, Kolmogorov, V., and Rother, C., “Graph cut based image segmentation with connectivity priors”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.

C. Rother, Kolmogorov, V., and Blake, A., “"GrabCut" - Interactive foreground extraction using iterated graph cuts”, in ACM Transactions on Graphics, 2004, vol. 23, pp. 309–314.

K. He, Rhemann, C., Rother, C., Tang, X., and Sun, J., “A global sampling method for alpha matting”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2011, pp. 2049–2056.

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.

H. Abu Alhaija, Mustikovela, S. K., Geiger, A., and Rother, C., “Geometric Image Synthesis”, ACCV. Proceedings, in press. 2018.

Technical Report (1.83 MB)

H. Abu Alhaija, Mustikovela, S. Karthik, Geiger, A., and Rother, C., “Geometric Image Synthesis”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11366 LNCS, pp. 85–100.

V. Gulshan, Rother, C., Criminisi, A., Blake, A., and Zisserman, A., “Geodesic star convexity for interactive image segmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 3129–3136.

F

V. Lempitsky, Roth, S., and Rother, C., “FusionFlow: Discrete-continuous optimization for optical flow estimation”, in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.

A. Blake, Criminisi, A., Cross, G., Kolmogorov, V., and Rother, C., “Fusion of stereo, colour and contrast”, Springer Tracts in Advanced Robotics, vol. 28, 2007.

V. Lempitsky, Rother, C., Roth, S., and Blake, A., “Fusion moves for markov random field optimization”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, pp. 1392–1405, 2010.

V. Lempitsky, Rother, C., Roth, S., and Blake, A., “Fusion moves for markov random field optimization”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, pp. 1392–1405, 2010.

L. Torresani, Kolmogorov, V., and Rother, C., “Feature correspondence via graph matching: Models and global optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, vol. 5303 LNCS, pp. 596–609.

L. Torresani, Kolmogorov, V., and Rother, C., “Feature correspondence via graph matching: Models and global optimization”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008, vol. 5303 LNCS, pp. 596–609.

A. Hosni, Rhemann, C., Bleyer, M., Rother, C., and Gelautz, M., “Fast cost-volume filtering for visual correspondence and beyond”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, pp. 504–511, 2013.

E

M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.

M. Bleyer, Rhemann, C., and Rother, C., “Extracting 3D scene-consistent object proposals and depth from stereo images”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, vol. 7576 LNCS, pp. 467–481.

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.

L. Ardizzone, Mackowiak, R., Rother, C., and Köthe, U., “Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling”, 2020.

PDF (2.87 MB)

A. Criminisi, Blake, A., Rother, C., Shotton, J., and Torr, P. H. S., “Efficient dense stereo with occlusions for new view-synthesis by four-state dynamic programming”, International Journal of Computer Vision, vol. 71, pp. 89–110, 2007.

D

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.

A. Sellen, Fogg, A., Aitken, M., Hodges, S., Rother, C., and Wood, K., “Do life-logging technologies support memory for the past? An experimental study using sensecam”, in Conference on Human Factors in Computing Systems - Proceedings, 2007, pp. 81–90.

U. Schmidt, Rother, C., Nowozin, S., Jancsary, J., and Roth, S., “Discriminative Non-blind Deblurring”, 2013.

C. Rother, Kumar, S., Kolmogorov, V., and Blake, A., “Digital tapestry [automatic image synthesis]”, in Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, 2005, vol. 1, pp. 589–596.

S. Ramos, Gehrig, S., Pinggera, P., Franke, U., and Rother, C., “Detecting unexpected obstacles for self-driving cars: Fusing deep learning and geometric modeling”, in IEEE Intelligent Vehicles Symposium, Proceedings, 2017, pp. 1025–1032.

M. Hornáček, Rhemann, C., Gelautz, M., and Rother, C., “Depth super resolution by rigid body self-similarity in 3D”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2013, pp. 1123–1130.

S. Zheng, Cheng, M. Ming, Warrell, J., Sturgess, P., Vineet, V., Rother, C., and Torr, P. H. S., “Dense semantic image segmentation with objects and attributes”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2014, pp. 3214–3221.

W. Li, Hosseini Jafari, O., and Rother, C., “Deep Object Co-segmentation”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11363 LNCS, pp. 638–653.

S. Nowozin, Rother, C., Bagon, S., Sharp, T., Yao, B., and Kohli, P., “Decision tree fields”, in Proceedings of the IEEE International Conference on Computer Vision, 2011, pp. 1668–1675.

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