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) 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.
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.
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.
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.
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.
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.
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) 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.
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.
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)