Publications
Conference Paper
Kleesiek, J, Biller, A, Urban, G, Köthe, U, Bendszus, M and Hamprecht, F A (2014).
ilastik for Multi-modal Brain Tumor Segmentation.
MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, 3rdplace. 12-17
Technical Report (405.91 KB) Krasowski, N, Beier, T, Knott, G W, Köthe, U, Hamprecht, F A and Kreshuk, A (2015).
Improving 3D EM Data Segmentation by Joint Optimization over Boundary Evidence and Biological Priors.
12th {IEEE} International Symposium on Biomedical Imaging, {ISBI} 2015, Brooklyn, NY, USA, April 16-19, 2015. 536-539
Technical Report (2.25 MB) Andres, B, Kappes, J H, Beier, T, Köthe, U and Hamprecht, F A (2012).
The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models.
Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}.
http://dx.doi.org/10.1007/978-3-642-33786-4_12 Technical Report (446.28 KB) Ommer, B and Buhmann, J M (2006).
Learning Compositional Categorization Models.
Proceedings of the European Conference on Computer Vision. Springer.
3953 316--329
Technical Report (1.35 MB) Antic, B and Ommer, B (2014).
Learning Latent Constituents for Recognition of Group Activities in Video.
Proceedings of the European Conference on Computer Vision (ECCV) (Oral). Springer. 33--47
Technical Report (4.54 MB) Diego, F and Hamprecht, F A (2013).
Learning Multi-Level Sparse Representation for Identifying Neuronal Activity.
Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS). Book of Abstracts Technical Report (1.05 MB) Jehle, M, Sommer, C and Jähne, B (2010).
Learning of Optimal Illumination for Material Classification.
Proceedings of the 32nd DAGM Symposium on Pattern Recognition, Darmstadt, Germany. Springer. 563-572
Ommer, B and Buhmann, J M (2007).
Learning the Compositional Nature of Visual Objects.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE. 1--8
Technical Report (2.78 MB) Ommer, B, Sauter, M and M., B J (2006).
Learning Top-Down Grouping of Compositional Hierarchies for Recognition.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Workshop on Perceptual Organization in Computer Vision. IEEE. 194--194
Technical Report (358.98 KB) Antic, B, Milbich, T and Ommer, B (2013).
Less is More: Video Trimming for Action Recognition.
Proceedings of the IEEE International Conference on Computer Vision, Workshop on Understanding Human Activities: Context and Interaction. IEEE. 515--521
Technical Report (984.89 KB) Ommer, B and Malik, J (2009).
Multi-scale Object Detection by Clustering Lines.
Proceedings of the IEEE International Conference on Computer Vision. IEEE. 484--491
Technical Report (3.18 MB) Hanselmann, M, Köthe, U, Renard, B Y, Kirchner, M, Heeren, R M A and Hamprecht, F A (2009).
Multivariate Watershed Segmentation of Compositional Data.
Proceedings of the 15th International Conference on Discrete Geometry for Computer Imagery (DGCI), in press. Springer.
5810 180-192
Technical Report (1.25 MB) Sigg, C, Fischer, B, Ommer, B, Roth, V and Buhmann, J M (2007).
Nonnegative CCA for Audiovisual Source Separation.
International Workshop on Machine Learning for Signal Processing. IEEE. 253--258
Technical Report (1.27 MB) Ommer, B and Buhmann, J M (2005).
Object Categorization by Compositional Graphical Models.
Proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition. Springer.
3757 235--250
Technical Report (2.07 MB) Kaster, F O, Kassemeyer, S, Merkel, B, Nix, O and Hamprecht, F A (2010).
An object-oriented library for systematic training and comparison of classifiers for computer-assisted tumor diagnosis from MRSI measurements.
Bildverarbeitung für die Medizin 2010 -- Algorithmen, Systeme, Anwendungen. Springer. 97-101
Technical Report (1.12 MB) Yarkony, J, Beier, T, Baldi, P and Hamprecht, F A (2014).
Parallel Multicut Segmentation via Dual Decomposition.
New Frontiers in Mining Complex Patterns - Third International Workshop, {NFMCP} 2014, Held in Conjunction with {ECML-PKDD} 2014, Nancy, France, September 19, 2014, Revised Selected Papers.
http://dx.doi.org/10.1007/978-3-319-17876-9_4 Antic, B and Ommer, B (2015).
Per-Sample Kernel Adaptation for Visual Recognition and Grouping.
Proceedings of the IEEE International Conference on Computer Vision. IEEE
Technical Report (1.58 MB) Andres, B, Köthe, U, Bonea, A, Nadler, B and Hamprecht, F A (2009).
Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times.
Pattern Recognition. 31st DAGM Symposium, Jena, Germany, September 9-11, 2009. Proceedings. Springer.
5748 502-511
Technical Report (3.08 MB) Eigenstetter, A, Takami, M and Ommer, B (2014).
Randomized Max-Margin Compositions for Visual Recognition.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE. 3590--3597
Technical Report (8.01 MB) Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2010).
Recognition and Analysis of Objects in Medieval Images.
Proceedins of the Aian Conference on Computer Vision, Workshop on e-Heritage. Springer. 296--305
Technical Report (2.76 MB) Rubio, J C and Ommer, B (2015).
Regularizing Max-Margin Exemplars by Reconstruction and Generative Models.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE. 4213--4221
Technical Report (2.8 MB) Antic, B and Ommer, B (2012).
Robust Multiple-Instance Learning with Superbags.
Proceedings of the Aian Conference on Computer Vision (ACCV) (Oral). Springer. 242--255
Technical Report (319.58 KB) Pages
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