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2016

Vianello, A, Manfredi, G, Diebold, M and Jähne, B (2016). 3D Reconstruction by a Combined Structure Tensor and Hough Transform Light-Field Approach. Forum Bildverarbeitung. https://doi.org/10.5445/KSP/1000059899

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

Proß, (2016). Analysis Of The Fetch Dependency Of The Slope Of Wind-Water Waves. Institut für Umweltphysik, Universität Heidelberg, Germany

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)

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

Pape, C (2016). Automatic Segmentation Of Neurites From Anisotropic Em-Imaging. University of Heidelberg

Prange, T (2016). Automatic Segmentation Of Neurons In Electron Microscopy Data With Membrane Defects. University of Heidelberg

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

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

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

Article (5.79 MB)

Baust, M, Weinmann, A, Wieczorek, M, Lasser, T, Storath, M and Navab, N (2016). Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging based on a Riemannian Manifold Approach. IEEE Transactions on Medical Imaging. 35 1972–1989

Technical Report (8.65 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

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}

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

Schmidt, P (2016). Deep Learning For Bioimage Analysis. University of Heidelberg

Balles, L (2016). Deep Learning For Diabetic Retinopathy Diagnostics. University of Heidelberg

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

Technical Report (1.14 MB)

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

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

Aström, F and Schnörr, C (2016). Double-Opponent Vectorial Total Variation. Proc. ECCV

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

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

Technical Report (4.89 MB)

Desana, M and Schnörr, C (2016). Expectation Maximization for Sum-Product Networks as Exponential Family Mixture Models. http://arxiv.org/abs/1604.07243

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

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

Technical Report (1.71 MB)

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

Technical Report (1.18 MB)

Aström, F and Schnörr, C (2016). A Geometric Approach to Color Image Regularization. https://arxiv.org/abs/1605.05977

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

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

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

Kappes, J, Speth, M, Reinelt, G and Schnörr, C (2016). Higher-order Segmentation via Multicuts. Comp. Vision Image Understanding. 143 104–119

Aström, F, Petra, S, Schmitzer, B and Schnörr, C (2016). Image Labeling by Assignment. http://arxiv.org/abs/1603.05285

Meijering, E, Carpenter, A E, Peng, H, Hamprecht, F A and Olivo-Marin, J (2016). Imagining the future of bioimage analysis. Nature Biotechnology. 34 1250-1255

Technical Report (924.57 KB)

Censor, Y, Gibali, A, Lenzen, F and Schnörr, C (2016). The Implicit Convex Feasibility Problem and Its Application to Adaptive Image Denoising. J. Comp. Math. 34 608-623

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

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