Publications

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

Technical Report (2.34 MB)

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

A. Stefanoiu, Weinmann, A., Storath, M., Navab, N., and Baust, M., “Joint Segmentation and Shape Regularization with a Generalized Forward Backward Algorithm”, IEEE Transactions on Image Processing, vol. 25, no. 7, pp. 3384 - 3394, 2016.

Technical Report (3.55 MB)

M. Schiegg, Diego, F., and Hamprecht, F. A., “Learning Diverse Models: The Coulomb Structured Support Vector Machine”, ECCV. Proceedings, vol. LNCS 9907. Springer, pp. 585-599, 2016.

Technical Report (2.54 MB)

M. von Borstel, “Learning to Count from Weak Supervision”, University of Heidelberg, 2016.

M. Diebold, “Light-Field Imaging and Heterogeneous Light Fields”, vol. Dissertation. IWR, Univ. Heidelberg, 2016.

P. Pinggera, Ramos, S., Gehrig, S., Franke, U., Rother, C., and Mester, R., “Lost and found: Detecting small road hazards for self-driving vehicles”, in IEEE International Conference on Intelligent Robots and Systems, 2016, vol. 2016-Novem, pp. 1099–1106.

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.

T. M. D. Strouse, “Marijuana's Public Health Pros and Cons | For Better | US News”, U.S. News and World Report, 2016.

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

J. Hendrik Kappes, Swoboda, P., Savchynskyy, B., Hazan, T., and Schnörr, C., “Multicuts and Perturb & MAP for Probabilistic Graph Clustering”, Journal of Mathematical Imaging and Vision, vol. 56, pp. 221–237, 2016.

J. H. Kappes, Swoboda, P., Savchynskyy, B., Hazan, T., and Schnörr, C., “Multicuts and Perturb & MAP for Probabilistic Graph Clustering”, J. Math. Imag. Vision, vol. 56, pp. 221–237, 2016.

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

M. Zisler, Kappes, J. H., Schnörr, C., Petra, S., and Schnörr, C., “Non-Binary Discrete Tomography by Continuous Non-Convex Optimization”, IEEE Comp. Imaging, vol. 2, pp. 335-347, 2016.

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

P. Swoboda, Shekhovtsov, A., Kappes, J. Hendrik, Schnörr, C., and Savchynskyy, B., “Partial Optimality by Pruning for MAP-Inference with General Graphical Models”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 38, pp. 1370–1382, 2016.

P. Swoboda, Shekhovtsov, A., Kappes, J. H., Schnörr, C., and Savchynskyy, B., “Partial Optimality by Pruning for MAP-Inference with General Graphical Models”, IEEE Trans. Patt. Anal. Mach. Intell., vol. 38, pp. 1370–1382, 2016.

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

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.

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

C. Haubold, Schiegg, M., Kreshuk, A., Berg, S., Köthe, U., and Hamprecht, F. A., “Segmenting and Tracking Multiple Dividing Targets Using ilastik”, in Focus on Bio-Image Informatics, vol. 219, Springer, 2016, pp. 199-229.

Technical Report (4.46 MB)

D. Rathore, “Semantic Segmentation Using Deep Learning”, University of Heidelberg, 2016.

K. Schwarz, “Spatio-Temporal Measurements of Water-Wave Height and Slope using Laser-Induced Fluorescence and Splines”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2016.

A. Sellent, Rother, C., and Roth, S., “Stereo video deblurring”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, vol. 9906 LNCS, pp. 558–575.

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

A. Kiem, “Structured Learning on Calcium Imaging Data”, University of Heidelberg, 2016.

F. Diego and Hamprecht, F. A., “Structured Regression Gradient Boosting”, CVPR. Proceedings. pp. 1459-1467, 2016.

Technical Report (3.97 MB)

F. Silvestri, Reinelt, G., and Schnörr, C., “Symmetry-free SDP Relaxations for Affine Subspace Clustering”. 2016.

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.

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

Technical Report (3.28 MB)

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

Technical Report (2.81 MB)

M. Haußmann, “Weakly Supervised Detection with Gaussian Processes”, University of Heidelberg, 2016.

Pages