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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. 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)

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.

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)

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.

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.

A. Biller, Badde, S., Nagel, A., Neumann, J. O., Wick, W., Hertenstein, A., Bendszus, M., Sahm, F., Benkhedah, N., and Kleesiek, J., “Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression”, American Journal of Neuroradiology, vol. 37 , pp. 66-73, 2016.

A. Biller, Badde, S., Nagel, A., Neumann, J. O., Wick, W., Hertenstein, A., Bendszus, M., Sahm, F., Benkhedah, N., and Kleesiek, J., “Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression”, American Journal of Neuroradiology, vol. 37 , pp. 66-73, 2016.

A. Biller, Badde, S., Nagel, A., Neumann, J. O., Wick, W., Hertenstein, A., Bendszus, M., Sahm, F., Benkhedah, N., and Kleesiek, J., “Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression”, American Journal of Neuroradiology, vol. 37 , pp. 66-73, 2016.

A. Biller, Badde, S., Nagel, A., Neumann, J. O., Wick, W., Hertenstein, A., Bendszus, M., Sahm, F., Benkhedah, N., and Kleesiek, J., “Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression”, American Journal of Neuroradiology, vol. 37 , pp. 66-73, 2016.

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

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)

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)

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

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

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.

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)

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)

2015

A. Biesdorf, Wörz, S., von Tengg-Kobligk, H., Rohr, K., and Schnörr, C., “3D Segmentation of Vessels by Incremental Implicit Polynomial Fitting and Convex Optimization”, in Proc.~ISBI, 2015.

Technical Report (611.33 KB)

E. Bodnariuc, Gurung, A., Petra, S., and Schnörr, C., “Adaptive Dictionary-Based Spatio-temporal Flow Estimation for Echo PIV”, in Proc.~EMMCVPR, 2015, vol. 8932, p. 378--391.

Technical Report (951.37 KB)

E. Bodnariuc, Gurung, A., Petra, S., and Schnörr, C., “Adaptive Dictionary-Based Spatio-temporal Flow Estimation for Echo PIV”, in EMMCVPR, 2015.

N. Krah, Testa, M., Brons, S., Jäkel, O., Parodi, K., Voss, B., and Rinaldi, I., “An advanced image processing method to improve the spatial resolution of ion radiographies”, Physics in Medicine and Biology, vol. 60, p. 8525, 2015.

N. Gianniotis, Schnörr, C., Molkenthin, C., and Bora, S. S., “Approximate variational inference based on a finite sample of Gaussian latent variables”, Patt.~Anal.~Appl., 2015.

Technical Report (1.4 MB)

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, Int.~J.~Comp.~Vision, 2015.

Technical Report (5.12 MB)

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, International Journal of Computer Vision, pp. 1-30, 2015.

Technical Report (1.5 MB)

J. H. Kappes, Andres, B., Hamprecht, F. A., Schnörr, C., Nowozin, S., Batra, D., Kim, S., Kausler, B. X., Kröger, T., Lellmann, J., Komodakis, N., Savchynskyy, B., and Rother, C., “A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems”, International Journal of Computer Vision, vol. 115, pp. 155–184, 2015.

A. Neufeld, Berger, J., Becker, F., Lenzen, F., and Schnörr, C., “Estimating Vehicle Ego-Motion and Piecewise Planar Scene Structure from Optical Flow in a Continuous Framework”, in 37th German Conference on Pattern Recognition, 2015.

A. Neufeld, Berger, J., Becker, F., Lenzen, F., and Schnörr, C., “Estimating Vehicle Ego-Motion and Piecewise Planar Scene Structure from Optical Flow in a Continuous Framework”, in 37th German Conference on Pattern Recognition, 2015.

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