Publications
W
Meister, S, Izadi, S, Kohli, P, Hämmerle, M, Rother, C and Kondermann, D (2012).
When Can We Use KinectFusion for Ground Truth Acquisition?.
Workshop on Color-Depth Camera Fusion in Robotics, IEEE International
Conference on Intelligent Robots and Systems U
Kirk, D S, Sellen, A J, Rother, C and Wood, K R (2006).
Understanding photowork.
Conference on Human Factors in Computing Systems - Proceedings.
2 761–770
Richmond, D, Kainmueller, D, Glocker, B, Rother, C and Myers, G (2015).
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).
9349 653–660
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
T
Schilling, H, Diebold, M, Rother, C and Jähne, B (2018).
Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 4530–4538
Glocker, B, T. Heibel, H, Navab, N, Kohli, P and Rother, C (2010).
TriangleFlow: Optical flow with triangulation-based higher-order likelihoods.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
6313 LNCS 272–285.
http://vision.middlebury.edu/flow/ S
Bleyer, M, Rother, C and Kohli, P (2010).
Surface stereo with soft segmentation.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1570–1577
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
Bleyer, M, Gelautz, M, Rother, C and Rhemann, C (2009).
A stereo approach that handles the matting problem via imagewarping.
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009.
2009 IEEE 501–508
Hornáček, M, Fitzgibbon, A and Rother, C (2014).
SphereFlow: 6 DoF scene flow from RGB-D pairs.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3526–3533
Rhemann, C, Rother, C, Kohli, P and Gelautz, M (2010).
A spatially varying PSF-based prior for alpha matting.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2149–2156
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 Zouhar, A, Rother, C and Fuchs, S (2015).
Semantic 3-D labeling of ear implants using a global parametric transition prior.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
9350 177–184
Mansfield, A, Gehler, P, Van Gool, L and Rother, C (2010).
Scene carving: Scene consistent image retargeting.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
6311 LNCS 143–156.
www.fujifilm.com/products/3d/camera/finepix_ R
Jancsary, J, Nowozin, S, Sharp, T and Rother, C (2012).
Regression Tree Fields An efficient, non-parametric approach to image labeling problems.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2376–2383
Jancsary, J, Nowozin, S, Sharp, T and Rother, C (2012).
Regression Tree Fields An efficient, non-parametric approach to image labeling problems.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2376–2383
Nair, R, Fitzgibbon, A, Kondermann, D and Rother, C (2015).
Reflection modeling for passive stereo.
Proceedings of the IEEE International Conference on Computer Vision.
2015 Inter 2291–2299
Gehler, P Vincent, Rother, C, Kiefel, M, Zhang, L and Schölkopf, B (2011).
Recovering intrinsic images with a global sparsity prior on reflectance.
Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 P
Pletscher, P, Nowozin, S, Kohli, P and Rother, C (2011).
Putting MAP back on the map.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
6835 LNCS 111–121
Pletscher, P, Nowozin, S, Kohli, P and Rother, C (2011).
Putting MAP back on the map.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
6835 LNCS 111–121
Rother, C, Carlsson, S and Tell, D (2002).
Projective factorization of planes and cameras in multiple views.
Proceedings - International Conference on Pattern Recognition.
16 737–740
Pages