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2017

S. Peter, Kirschbaum, E., Both, M., Campbell, L. A., Harvey, B. K., Heins, C., Durstewitz, D., Diego, F., and Hamprecht, F. A., “Sparse convolutional coding for neuronal assembly detection”, NIPS, poster. 2017.

A. Rennebaum, “Spatio-Temporal Properties of the initial Wave Formation Phase at the Aeolotron”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2017.

T. Milbich, Bautista, M., Sutter, E., and Ommer, B., “Unsupervised Video Understanding by Reconciliation of Posture Similarities”, in Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017.

M. Haußmann, Hamprecht, F. A., and Kandemir, M., “Variational Bayesian Multiple Instance Learning with Gaussian Processes”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 6570-6579, 2017.

Technical Report (1.29 MB)

N. von Schmude, “Visual Localization with Lines”, vol. Dissertation. IWR, Univ. Heidelberg, 2017.

2016

A. Vianello, Manfredi, G., Diebold, M., and Jähne, B., “3D Reconstruction by a Combined Structure Tensor and Hough Transform Light-Field Approach”, Forum Bildverarbeitung. 2016.

J. Kunz and Jähne, B., “Active thermography as a tool to investigate heat and gas transfer across the air-water interface”, in 13th Quantitative Infrared Thermographie Conference (QIRT 2016), Gdansk 4–8 July 2016, 2016.

C. Proß, “Analysis of the Fetch Dependency of the Slope of Wind-Water Waves”, Institut für Umweltphysik, Universität Heidelberg, Germany, 2016.

F. Aström, Petra, S., Schmitzer, B., and Schnörr, C., “The Assignment Manifold: A Smooth Model for Image Labeling”, in Proc. 2nd Int. Workshop on Differential Geometry in Computer Vision and Machine Learning (DIFF-CVML'16; oral presentation; Grenander best paper award), 2016.

N. Krasowski, “Automated Segmentation for Connectomics Utilizing Higher-Order Biological Priors”. University of Heidelberg, 2016.

C. Pape, “Automatic Segmentation of Neurites from Anisotropic EM-Imaging”, University of Heidelberg, 2016.

T. Prange, “Automatic Segmentation of Neurons in Electron Microscopy Data with Membrane Defects”, University of Heidelberg, 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.

S. Wolf, “Cell Tracking With Graphical Model Using Higher Order Features On Track Segments”, University of Heidelberg, 2016.

M. Bautista, Sanakoyeu, A., Sutter, E., and Ommer, B., “CliqueCNN: Deep Unsupervised Exemplar Learning”, in Proceedings of the Conference on Advances in Neural Information Processing Systems (NIPS), Barcelona, 2016.

Article (5.79 MB)

M. Baust, Weinmann, A., Wieczorek, M., Lasser, T., Storath, M., and Navab, N., “Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging based on a Riemannian Manifold Approach”, IEEE Transactions on Medical Imaging, vol. 35, no. 8, pp. 1972–1989, 2016.

Technical Report (8.65 MB)

L. A. Royer, Richmond, D. L., Rother, C., Andres, B., and Kainmueller, D., “Convexity shape constraints for image segmentation”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016, vol. 2016-Decem, pp. 402–410.

B. Güssefeld, Honauer, K., and Kondermann, D., “Creating Feasible Reflectance Data for Synthetic Optical Flow Datasets”, in Advances in Visual Computing - 12th International Symposium, {ISVC} 2016, Las Vegas, NV, USA, December 12-14, 2016, Proceedings, Part {I}, 2016.

K. Honauer, Johannsen, O., Kondermann, D., and Goldlücke, B., “A Dataset and Evaluation Methodology for Depth Estimation on 4D Light Fields”, in Computer Vision - ACCV 2016 : 13th Asian Conference on Computer Vision, Taipei, Taiwan, November 20-24, 2016, Revised Selected Papers, Part III, Cham, 2016.

P. Schmidt, “Deep Learning for Bioimage Analysis”, University of Heidelberg, 2016.

L. Balles, “Deep Learning for Diabetic Retinopathy Diagnostics”, University of Heidelberg, 2016.

J. Kleesiek, Urban, G., Hubert, A., Schwarz, D., Maier-Hein, K., Bendszus, M., and Biller, A., “Deep MRI brain extraction: A 3D convolutional neural network for skull stripping.”, NeuroImage, vol. 129, pp. 460-469, 2016.

Technical Report (1.14 MB)

P. Bell and Ommer, B., “Digital Connoisseur? How Computer Vision Supports Art History”, in Connoisseurship nel XXI secolo. Approcci, Limiti, Prospettive, A. Aggujaro & S. Albl (ed.), Rome: Artemide, 2016.

M. Zisler, Petra, S., Schnörr, C., and Schnörr, C., “Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints”, in Proc. GCPR, 2016.

F. Aström and Schnörr, C., “Double-Opponent Vectorial Total Variation”, in Proc. ECCV, 2016.

P. Swoboda, Kuske, J., and Savchynskyy, B., “A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems”, arXiv, preprint, 2016.

T. Beier, Andres, B., Köthe, U., and Hamprecht, F. A., “An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem”, ECCV. Proceedings, vol. LNCS 9906. Springer, pp. 715-730, 2016.

Technical Report (4.89 MB)

M. Desana and Schnörr, C., “Expectation Maximization for Sum-Product Networks as Exponential Family Mixture Models”. 2016.

H. Schilling, Diebold, M., Gutsche, M., Aziz-Ahmad, H., and Jähne, B., “A fractal calibration pattern for improved camera calibration”, Forum Bildverarbeitung. 2016.

M. von Borstel, Kandemir, M., Schmidt, P., Rao, M., Rajamani, K., and Hamprecht, F. A., “Gaussian process density counting from weak supervision”, ECCV. Proceedings, vol. LNCS 9905. Springer, pp. 365-380 , 2016.

Technical Report (1.71 MB)

C. Haubold, Ales, J., Wolf, S., and Hamprecht, F. A., “A Generalized Successive Shortest Paths Solver for Tracking Dividing Targets”, ECCV. Proceedings, vol. LNCS 9911. Springer, pp. 566-582, 2016.

Technical Report (1.18 MB)

F. Aström and Schnörr, C., “A Geometric Approach to Color Image Regularization”. 2016.

F. Aström, Petra, S., Schmitzer, B., and Schnörr, C., “A Geometric Approach to Image Labeling”, in Proc. ECCV, 2016.

D. Kondermann, Nair, R., Honauer, K., Krispin, K., Andrulis, J., Brock, A., Güssefeld, B., Rahimimoghaddam, M., Hofmann, S., Brenner, C., and Jähne, B., “The HCI Benchmark Suite: Stereo and Flow Ground Truth With Uncertainties for Urban Autonomous Driving”, in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016.

M. Diebold, Gatto, A., and Jähne, B., “Heterogeneous Light Fields”, in 2016 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2016, Las Vegas, NV, USA, June 27-30, 2016, 2016.

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