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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 icon PDF (9.95 MB)
2019
B. Jähne, “Air-Sea Gas Exchange”, Encyclopedia of Ocean Sciences, vol. 6. Academic Press, pp. 1–13, 2019.
2017
O. Hosseini Jafari, Groth, O., Kirillov, A., Yang, M. Ying, and Rother, C., “Analyzing modular CNN architectures for joint depth prediction and semantic segmentation”, in Proceedings - IEEE International Conference on Robotics and Automation, 2017, pp. 4620–4627.
M. Hullin, Klein, R., Schultz, T., Yao, A., Li, W., Hosseini Jafari, O., and Rother, C., “Semantic-Aware Image Smoothing”, Vision, Modeling, and Visualization, 2017.
2016
S. Karthik Mustikovela, Yang, M. Ying, and Rother, C., “Can ground truth label propagation from video help semantic segmentation?”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, vol. 9915 LNCS, pp. 804–820.
D. L. Richmond, Kainmueller, D., Yang, M. Y., Myers, E. W., and Rother, C., “Mapping auto-context decision forests to deep convnets for semantic segmentation”, in British Machine Vision Conference 2016, BMVC 2016, 2016, vol. 2016-Septe, pp. 144.1–144.12.
D. L. Richmond, Kainmueller, D., Yang, M. Y., Myers, E. W., and Rother, C., “Mapping auto-context decision forests to deep convnets for semantic segmentation”, in British Machine Vision Conference 2016, BMVC 2016, 2016, vol. 2016-Septe, pp. 144.1–144.12.
D. L. Richmond, Kainmueller, D., Yang, M. Y., Myers, E. W., and Rother, C., “Mapping auto-context decision forests to deep convnets for semantic segmentation”, in British Machine Vision Conference 2016, BMVC 2016, 2016, vol. 2016-Septe, pp. 144.1–144.12.
O. Hosseini Jafari and Yang, M. Ying, “Real-time RGB-D based template matching pedestrian detection”, in Proceedings - IEEE International Conference on Robotics and Automation, 2016, vol. 2016-June, pp. 5520–5527.
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
P. Yarlagadda and Ommer, B., “Beyond the Sum of Parts: Voting with Groups of Dependent Entities”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, p. 1134--1147, 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.
2014
C. Zhang, Yarkony, J., and Hamprecht, F. A., “Cell detection and segmentation using correlation clustering”, in MICCAI. Proceedings, 2014, pp. 9-16.PDF icon Technical Report (8.06 MB)
J. Yarkony, Zhang, C., and Fowlkes, C. C., “Hierarchical Planar Correlation Clustering for Cell Segmentation”, in EMMCVPR. Proceedings, 2014, vol. 8932, pp. 492-504.PDF icon Technical Report (548.12 KB)
J. Yarkony, Beier, T., Baldi, P., and Hamprecht, F. A., “Parallel Multicut Segmentation via Dual Decomposition”, in New Frontiers in Mining Complex Patterns - Third International Workshop, {NFMCP} 2014, Held in Conjunction with {ECML-PKDD} 2014, Nancy, France, September 19, 2014, Revised Selected Papers, 2014.
2013
P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Towards a Computer-based Understanding of Medieval Images”, in Scientific Computing & Cultural Heritage, Springer, 2013, p. 89--97.
2012
P. Yarlagadda and Ommer, B., “From Meaningful Contours to Discriminative Object Shape”, in Proceedings of the European Conference on Computer Vision, 2012, vol. 7572, p. 766--779.PDF icon Technical Report (4.58 MB)
P. Yarlagadda, Eigenstetter, A., and Ommer, B., “Learning Discriminative Chamfer Regularization”, in BMVC, 2012, p. 1--11.
A. Eigenstetter, Yarlagadda, P., and Ommer, B., “Max-Margin Regularization for Reducing Accidentalness in Chamfer Matching”, in Proceedins of the Aian Conference on Computer Vision, 2012, p. 152--163.PDF icon Technical Report (7.31 MB)
2011
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.
P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Top-down Analysis of Low-level Object Relatedness Leading to Semantic Understanding of Medieval Image Collections”, in Conference on Computer Vision and Image Analysis of Art II, 2011, vol. 7869, p. 61--69.PDF icon Technical Report (11.06 MB)
L. Maier-Hein, Franz, A. M., Fangerau, M., Schmidt, M., Seitel, A., Mersmann, S., Kilgus, T., Groch, A., Yung, K., Santos, T. R. dos, and Meinzer, H. - P., “Towards mobile augmented reality for on-patient visualization of medical images”, in Bildverarbeitung für die Medizin (2011), 2011, p. 389--393.
2010
L. Ding and Yilmaz, A., “Interactive image segmentation using probabilistic hypergraphs”, Pattern Recognition, vol. 43, pp. 1863–1873, 2010.
P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Recognition and Analysis of Objects in Medieval Images”, in Proceedins of the Aian Conference on Computer Vision, Workshop on e-Heritage, 2010, p. 296--305.PDF icon Technical Report (2.76 MB)
P. Yarlagadda, Monroy, A., and Ommer, B., “Voting by Grouping Dependent Parts”, in Proceedings of the European Conference on Computer Vision, 2010, vol. 6315, p. 197--210.PDF icon Technical Report (2.99 MB)
2009
J. Yuan, Schnörr, C., and Steidl, G., “Convex Hodge Decomposition and Regularization of Image Flows”, J.~Math.~Imag.~Vision, vol. 33, pp. 169-177, 2009.PDF icon Technical Report (1003.75 KB)
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., Schnörr, C., Mórken, K., and Lysaker, M., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 150-162.PDF icon Technical Report (1.75 MB)
J. Yuan, Schnörr, C., and Steidl, G., “Total-Variation Based Piecewise Affine Regularization”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 552-564.PDF icon Technical Report (478.04 KB)
J. Yuan, Schnörr, C., and Steidl, G., “Total-Variation Based Piecewise Affine Regularization”, in Scale Space and Variational Methods in Computer Vision (SSVM 2009), 2009, vol. 5567, pp. 552-564.
P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Towards a Computer-based Understanding of Medieval Images”, in Scientific Computing & Cultural Heritage, 2009, p. 89--97.
2008
J. Yuan, Steidl, G., and Schnörr, C., “Convex Hodge Decomposition of Image Flows”, in Pattern Recognition -- 30th DAGM Symposium, 2008, vol. 5096, p. 416--425.PDF icon Technical Report (290.72 KB)
J. Lellmann, Kappes, J. H., Yuan, J., Becker, F., and Schnörr, C., “Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation”, IWR, University of Heidelberg, 2008.PDF icon Technical Report (2.6 MB)

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