Publications

Berger, J and Schnörr, C (2016). Joint Recursive Monocular Filtering of Camera Motion and Disparity Map. 38th German Conference on Pattern Recognition. Springer, Hannover. https://arxiv.org/abs/1606.02092

Technical Report (2.34 MB)

Berger, J and Schnörr, C (2016). Joint Recursive Monocular Filtering of Camera Motion and Disparity Map. 38th German Conference on Pattern Recognition

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

Technical Report (3.55 MB)

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

Technical Report (2.54 MB)

von Borstel, M (2016). Learning To Count From Weak Supervision. University of Heidelberg

Diebold, M (2016). Light-Field Imaging and Heterogeneous Light Fields. IWR, Univ. Heidelberg. Dissertation

Pinggera, P, Ramos, S, Gehrig, S, Franke, U, Rother, C and Mester, R (2016). Lost and found: Detecting small road hazards for self-driving vehicles. IEEE International Conference on Intelligent Robots and Systems. 2016-Novem 1099–1106. http://www.6d-vision.com/lostandfounddataset

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

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. https://github.com/BVLC/caffe/wiki/Model-Zoo\#fcn

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

Strouse, T M D (2016). Marijuana's Public Health Pros and Cons | For Better | US News. U.S. News and World Report. http://health.usnews.com/health-news/patient-advice/articles/2016-10-12/marijuanas-public-health-pros-and-cons

Lenor, S (2016). Model-Based Estimation of Meteorological Visibility in the Context of Automotive Camera Systems. IWR, Univ. Heidelberg. Dissertation

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

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

Jähne, B and Schwarzbauer, M (2016). Noise equalisation and quasi loss-less image data compression – or how many bits needs an image sensor?. tm – Technisches Messen. 83 16–24

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

Bodnariuc, E, Petra, S, Poelma, C and Schnörr, C (2016). Parametric Dictionary-Based Velocimetry for Echo PIV. Proc. CGPR

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

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

Bodnariuc, E, Schiffner, M F, Petra, S and Schnörr, C (2016). Plane Wave Acoustic Superposition for Fast Ultrasound Imaging. International Ultrasonics Symposium

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

von Schmude, N, Lothe, P and Jähne, B (2016). Relative Pose Estimation from Straight Lines using Parallel Line Clustering and its Application to Monocular Visual Odometry. Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

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

Technical Report (4.46 MB)

Rathore, D (2016). Semantic Segmentation Using Deep Learning. University of Heidelberg

Schwarz, K (2016). Spatio-Temporal Measurements Of Water-Wave Height And Slope Using Laser-Induced Fluorescence And Splines. Institut für Umweltphysik, Universität Heidelberg, Germany

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

Sellent, A, Rother, C and Roth, S (2016). Stereo Video Deblurring-Supplemental Material

Kiem, A (2016). Structured Learning On Calcium Imaging Data. University of Heidelberg

Diego, F and Hamprecht, F A (2016). Structured Regression Gradient Boosting. CVPR. Proceedings. 1459-1467

Technical Report (3.97 MB)

Silvestri, F, Reinelt, G and Schnörr, C (2016). Symmetry-free SDP Relaxations for Affine Subspace Clustering. http://arxiv.org/abs/1607.07387

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

Kandemir, M, Haußmann, M, Diego, F, Rajamani, K, van der Laak, J and Hamprecht, F A (2016). Variational weakly-supervised Gaussian processes. BMVC. Proceedings

Technical Report (3.28 MB)

Kleesiek, J, Petersen, J, Döring, M, Maier-Hein, K, Köthe, U, Wick, W, Hamprecht, F A, Bendszus, M and Biller, A (2016). Virtual Raters for Reproducible and Objective Assessments in Radiology. Nature Scientific Reports. 6

Technical Report (2.81 MB)

Haußmann, (2016). Weakly Supervised Detection With Gaussian Processes. University of Heidelberg

Pages