All Publications

2016
Diebold, M, Gatto, A and Jähne, B (2016). Heterogeneous Light Fields. 2016 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2016, Las Vegas, NV, USA, June 27-30, 2016. http://dx.doi.org/10.1109/CVPR.2016.193 DOI Google Scholar BibTeX RTF EndNote XML
Zisler, M, Kappes, J H, Schnörr, C, Petra, S and Schnörr, C (2016). Non-Binary Discrete Tomography by Continuous Non-Convex Optimization. IEEE Comp. Imaging. 2 335-347 Google Scholar BibTeX RTF EndNote XML
Beier, T, Andres, B, Köthe, U and Hamprecht, F A (2016). An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem. ECCV. Proceedings. Springer. LNCS 9906 715-730 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (4.89 MB)
Schilling, H, Diebold, M, Gutsche, M, Aziz-Ahmad, H and Jähne, B (2016). A fractal calibration pattern for improved camera calibration. Forum Bildverarbeitung. https://doi.org/10.5445/KSP/1000059899 DOI Google Scholar BibTeX RTF EndNote XML
Silvestri, F, Reinelt, G and Schnörr, C (2016). Symmetry-free SDP Relaxations for Affine Subspace Clustering. http://arxiv.org/abs/1607.07387 Google Scholar BibTeX RTF EndNote XML
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 DOI Google Scholar BibTeX RTF EndNote XML
Biller, A, Badde, S, Nagel, A, Neumann, J O, Wick, W, Hertenstein, A, Bendszus, M, Sahm, F, Benkhedah, N and Kleesiek, J (2016). Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression. American Journal of Neuroradiology. 37 66-73 DOI Google Scholar BibTeX RTF EndNote XML
Rathore, D (2016). Semantic Segmentation Using Deep Learning. University of Heidelberg Google Scholar BibTeX RTF EndNote XML
Berger, J and Schnörr, C (2016). Joint Recursive Monocular Filtering of Camera Motion and Disparity Map. 38th German Conference on Pattern Recognition Google Scholar BibTeX RTF EndNote XML
Richmond, D L, Kainmueller, D, Yang, M Y, Myers, E W and Rother, C (2016). Mapping auto-context decision forests to deep convnets for semantic segmentation. British Machine Vision Conference 2016, BMVC 2016. 2016-Septe 144.1–144.12. http://arxiv.org/abs/1507.07583 DOI Google Scholar BibTeX RTF EndNote XML
Swoboda, P, Shekhovtsov, A, Kappes, J Hendrik, Schnörr, C and Savchynskyy, B (2016). Partial Optimality by Pruning for MAP-Inference with General Graphical Models. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE Computer Society. 38 1370–1382 DOI Google Scholar BibTeX RTF EndNote XML
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 DOI Google Scholar BibTeX RTF EndNote XML
Prange, T (2016). Automatic Segmentation Of Neurons In Electron Microscopy Data With Membrane Defects. University of Heidelberg Google Scholar BibTeX RTF EndNote XML
Diego, F and Hamprecht, F A (2016). Structured Regression Gradient Boosting. CVPR. Proceedings. 1459-1467 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (3.97 MB)
Bautista, M, Sanakoyeu, A, Sutter, E and Ommer, B (2016). CliqueCNN: Deep Unsupervised Exemplar Learning. Proceedings of the Conference on Advances in Neural Information Processing Systems (NIPS). MIT Press, Barcelona. https://arxiv.org/abs/1608.08792 Google Scholar BibTeX RTF EndNote XML Article (5.79 MB)
Kondermann, D, Nair, R, Honauer, K, Krispin, K, Andrulis, J, Brock, A, Güssefeld, B, Rahimimoghaddam, M, Hofmann, S, Brenner, C and Jähne, B (2016). The HCI Benchmark Suite: Stereo and Flow Ground Truth With Uncertainties for Urban Autonomous Driving. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops Google Scholar BibTeX RTF EndNote XML
Kappes, J H, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2016). Multicuts and Perturb & MAP for Probabilistic Graph Clustering. J. Math. Imag. Vision. 56 221–237 Google Scholar BibTeX RTF EndNote XML
Kappes, J Hendrik, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2016). Multicuts and Perturb & MAP for Probabilistic Graph Clustering. Journal of Mathematical Imaging and Vision. 56 221–237. http://arxiv.org/abs/1601.02088 DOI Google Scholar BibTeX RTF EndNote XML
Haubold, C, Ales, J, Wolf, S and Hamprecht, F A (2016). A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets. ECCV. Proceedings. Springer. LNCS 9911 566-582 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (1.18 MB)
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 DOI Google Scholar BibTeX RTF EndNote XML
Kleesiek, J, Urban, G, Hubert, A, Schwarz, D, Maier-Hein, K, Bendszus, M and Biller, A (2016). Deep MRI brain extraction: A 3D convolutional neural network for skull stripping.. NeuroImage. 129 460-469 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (1.14 MB)
Schmidt, P (2016). Deep Learning For Bioimage Analysis. University of Heidelberg Google Scholar BibTeX RTF EndNote XML
Zisler, M, Petra, S, Schnörr, C and Schnörr, C (2016). Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints. Proc. GCPR Google Scholar BibTeX RTF EndNote XML
von Borstel, M (2016). Learning To Count From Weak Supervision. University of Heidelberg Google Scholar BibTeX RTF EndNote XML
Desana, M and Schnörr, C (2016). Expectation Maximization for Sum-Product Networks as Exponential Family Mixture Models. http://arxiv.org/abs/1604.07243 Google Scholar BibTeX RTF EndNote XML
Sellent, A, Rother, C and Roth, S (2016). Stereo Video Deblurring-Supplemental Material Google Scholar BibTeX RTF EndNote XML
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 Google Scholar BibTeX RTF EndNote XML
Stefanoiu, A, Weinmann, A, Storath, M, Navab, N and Baust, M (2016). Joint Segmentation and Shape Regularization with a Generalized Forward Backward Algorithm. IEEE Transactions on Image Processing. 25 3384 - 3394 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (3.55 MB)
Krasowski, N (2016). Automated Segmentation for Connectomics Utilizing Higher-Order Biological Priors. University of Heidelberg Google Scholar BibTeX RTF EndNote XML
Güssefeld, B, Honauer, K and Kondermann, D (2016). Creating Feasible Reflectance Data for Synthetic Optical Flow Datasets. Advances in Visual Computing - 12th International Symposium, {ISVC} 2016, Las Vegas, NV, USA, December 12-14, 2016, Proceedings, Part {I}. http://dx.doi.org/10.1007/978-3-319-50835-1_8 DOI Google Scholar BibTeX RTF EndNote XML
Swoboda, P, Shekhovtsov, A, Kappes, J H, Schnörr, C and Savchynskyy, B (2016). Partial Optimality by Pruning for MAP-Inference with General Graphical Models. IEEE Trans. Patt. Anal. Mach. Intell. 38 1370–1382 Google Scholar BibTeX RTF EndNote XML
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 DOI Google Scholar BibTeX RTF EndNote XML
Schiegg, M, Diego, F and Hamprecht, F A (2016). Learning Diverse Models: The Coulomb Structured Support Vector Machine. ECCV. Proceedings. Springer. LNCS 9907 585-599 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (2.54 MB)
Haußmann, (2016). Weakly Supervised Detection With Gaussian Processes. University of Heidelberg Google Scholar BibTeX RTF EndNote XML
Bodnariuc, E, Petra, S, Poelma, C and Schnörr, C (2016). Parametric Dictionary-Based Velocimetry for Echo PIV. Proc. CGPR Google Scholar BibTeX RTF EndNote XML
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 DOI Google Scholar BibTeX RTF EndNote XML
Swoboda, P, Kuske, J and Savchynskyy, B (2016). A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems. arXiv, preprint. https://arxiv.org/pdf/1612.05460.pdf Google Scholar BibTeX RTF EndNote XML
Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). The Assignment Manifold: A Smooth Model for Image Labeling. Proc. 2nd Int. Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16; oral presentation; Grenander best paper award) Google Scholar BibTeX RTF EndNote XML
Hosseini Jafari, O and Yang, M Ying (2016). Real-time RGB-D based template matching pedestrian detection. Proceedings - IEEE International Conference on Robotics and Automation. 2016-June 5520–5527 DOI Google Scholar BibTeX RTF EndNote XML
Haubold, C, Schiegg, M, Kreshuk, A, Berg, S, Köthe, U and Hamprecht, F A (2016). Segmenting and Tracking Multiple Dividing Targets Using ilastik. Focus on Bio-Image Informatics. Springer. 219 199-229 DOI Google Scholar BibTeX RTF EndNote XML Technical Report (4.46 MB)

All Publications

2016

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