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2019
Sanakoyeu, A, Tschernezki, V, Büchler, U and Ommer, B (2019). Divide and Conquer the Embedding Space for Metric Learning. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://github.com/CompVis/metric-learning-divide-and-conquer
Brachmann, E and Rother, C (2019). Expert sample consensus applied to camera re-localization. Proceedings of the IEEE International Conference on Computer Vision. 2019-Octob 7524–7533. http://arxiv.org/abs/1908.02484
Berg, S, Kutra, D, Kroeger, T, Straehle, C N, Kausler, B X, Haubold, C, Schiegg, M, Ales, J, Beier, T, Rudy, M, Eren, K, Cervantes, J I, Xu, B, Beuttenmüller, F, Wolny, A, Zhang, C, Köthe, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232
Berg, S, Kutra, D, Kroeger, T, Straehle, C N, Kausler, B X, Haubold, C, Schiegg, M, Ales, J, Beier, T, Rudy, M, Eren, K, Cervantes, J I, Xu, B, Beuttenmüller, F, Wolny, A, Zhang, C, Köthe, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232
Berg, S, Kutra, D, Kroeger, T, Straehle, C N, Kausler, B X, Haubold, C, Schiegg, M, Ales, J, Beier, T, Rudy, M, Eren, K, Cervantes, J I, Xu, B, Beuttenmüller, F, Wolny, A, Zhang, C, Köthe, U, Hamprecht, F A and Kreshuk, A (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16 1226-1232
Hosseini Jafari, O, Mustikovela, S Karthik, Pertsch, K, Brachmann, E and Rother, C (2019). iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11363 LNCS 477–492
Bengio, Y, Deleu, T, Rahaman, N, Ke, R, Lachapelle, S, Bilaniuk, O, Goyal, A and Pal, C (2019). A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. arXiv preprint arXiv:1901.10912PDF icon Technical Report (871.59 KB)
Bengio, Y, Deleu, T, Rahaman, N, Ke, R, Lachapelle, S, Bilaniuk, O, Goyal, A and Pal, C (2019). A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. arXiv preprint arXiv:1901.10912PDF icon Technical Report (871.59 KB)
Brattoli, B, Roth, K and Ommer, B (2019). MIC: Mining Interclass Characteristics for Improved Metric Learning. Proceedings of the Intl. Conf. on Computer Vision (ICCV)
Brachmann, E and Rother, C (2019). Neural-guided RANSAC: Learning where to sample model hypotheses. Proceedings of the IEEE International Conference on Computer Vision. 2019-Octob 4321–4330. http://arxiv.org/abs/1905.04132PDF icon PDF (8.02 MB)
Bhowmik, A, Gumhold, S, Rother, C and Brachmann, E (2019). Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task. http://arxiv.org/abs/1912.00623
Bhowmik, A, Gumhold, S, Rother, C and Brachmann, E (2019). Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task. http://arxiv.org/abs/1912.00623
Esposito, M, Hennersperger, C, Göbl, R, Demaret, L, Storath, M, Navab, N, Baust, M and Weinmann, A (2019). Total variation regularization of pose signals with an application to 3D freehand ultrasound. IEEE Transactions on Medical Imaging. 38(10) 2245-2258
Lorenz, D, Bereska, L, Milbich, T and Ommer, B (2019). Unsupervised Part-Based Disentangling of Object Shape and Appearance. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Oral + Best paper finalist: top 45 / 5160 submissions)
2018
Bopp, M (2018). Air-Flow and Stress Partitioning over Wind Waves in a Linear Wind-Wave Facility. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, Heidelberg. Dissertation
Hodaň, T, Michel, F, Brachmann, E, Kehl, W, Buch, A Glent, Kraft, D, Drost, B, Vidal, J, Ihrke, S, Zabulis, X, Sahin, C, Manhardt, F, Tombari, F, Kim, T Kyun, Matas, J and Rother, C (2018). BOP: Benchmark for 6D object pose estimation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11214 LNCS 19–35. http://arxiv.org/abs/1808.08319
Hodaň, T, Michel, F, Brachmann, E, Kehl, W, Buch, A Glent, Kraft, D, Drost, B, Vidal, J, Ihrke, S, Zabulis, X, Sahin, C, Manhardt, F, Tombari, F, Kim, T Kyun, Matas, J and Rother, C (2018). BOP: Benchmark for 6D object pose estimation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11214 LNCS 19–35. http://arxiv.org/abs/1808.08319
Bell, P and Ommer, B (2018). Computer Vision und Kunstgeschichte — Dialog zweier Bildwissenschaften. Computing Art Reader: Einführung in die digitale Kunstgeschichte, P. Kuroczyński et al. (ed.)PDF icon 413-17-83318-2-10-20181210.pdf (2.98 MB)
Sayed, N, Brattoli, B and Ommer, B (2018). Cross and Learn: Cross-Modal Self-Supervision. German Conference on Pattern Recognition (GCPR) (Oral). Stuttgart, Germany. https://arxiv.org/abs/1811.03879v1PDF icon Article (891.47 KB)PDF icon Oral slides (9.17 MB)
Sanakoyeu, A, Bautista, M and Ommer, B (2018). Deep Unsupervised Learning of Visual Similarities. Pattern Recognition. 78. https://authors.elsevier.com/a/1WXUt77nKSb25 PDF icon PDF (8.35 MB)
Wahl, A - S, Erlebach, E, Brattoli, B, Büchler, U, Kaiser, J, Ineichen, V B, Mosberger, A C, Schneeberger, S, Imobersteg, S, Wieckhorst, M, Stirn, M, Schroeter, A, Ommer, B and Schwab, M E (2018). Early reduced behavioral activity induced by large strokes affects the efficiency of enriched environment in rats. Sage Journals. Journal of Cerebral Blood Flow & Metabolism. http://journals.sagepub.com/doi/abs/10.1177/0271678X18777661PDF icon 0271678x18777661.pdf (770.87 KB)
Wahl, A - S, Erlebach, E, Brattoli, B, Büchler, U, Kaiser, J, Ineichen, V B, Mosberger, A C, Schneeberger, S, Imobersteg, S, Wieckhorst, M, Stirn, M, Schroeter, A, Ommer, B and Schwab, M E (2018). Early reduced behavioral activity induced by large strokes affects the efficiency of enriched environment in rats. Sage Journals. Journal of Cerebral Blood Flow & Metabolism. http://journals.sagepub.com/doi/abs/10.1177/0271678X18777661PDF icon 0271678x18777661.pdf (770.87 KB)
Büchler, U, Brattoli, B and Ommer, B (2018). Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning. Proceedings of the European Conference on Computer Vision (ECCV). (UB and BB contributed equally), Munich, GermanyPDF icon Article (5.34 MB)PDF icon buechler_eccv18_poster.pdf (1.65 MB)
Büchler, U, Brattoli, B and Ommer, B (2018). Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning. Proceedings of the European Conference on Computer Vision (ECCV). (UB and BB contributed equally), Munich, GermanyPDF icon Article (5.34 MB)PDF icon buechler_eccv18_poster.pdf (1.65 MB)
Hosseini Jafari, O, Mustikovela, S K, Pertsch, K, Brachmann, E and Rother, C (2018). iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects. ACCV. Proceedings, in pressPDF icon Technical Report (3.28 MB)
Brachmann, E and Rother, C (2018). Learning Less is More - 6D Camera Localization via 3D Surface Regression. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 4654–4662. http://arxiv.org/abs/1711.10228
Ghori, O, Mackowiak, R, Bautista, M, Beuter, N, Drumond, L, Diego, F and Ommer, B (2018). Learning to Forecast Pedestrian Intention from Pose Dynamics. Intelligent Vehicles, IEEE, 2018
Ghori, O, Mackowiak, R, Bautista, M, Beuter, N, Drumond, L, Diego, F and Ommer, B (2018). Learning to Forecast Pedestrian Intention from Pose Dynamics. Intelligent Vehicles, IEEE, 2018
Erb, W, Weinmann, A, Ahlborg, M, Brandt, C, Bringout, G, Buzug, T M, Frikel, J, Kaethner, C, Knopp, T, März, T, Möddel, M, Storath, M and Weber, A (2018). Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging. Inverse Problems. 34
Erb, W, Weinmann, A, Ahlborg, M, Brandt, C, Bringout, G, Buzug, T M, Frikel, J, Kaethner, C, Knopp, T, März, T, Möddel, M, Storath, M and Weber, A (2018). Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging. Inverse Problems. 34
Erb, W, Weinmann, A, Ahlborg, M, Brandt, C, Bringout, G, Buzug, T M, Frikel, J, Kaethner, C, Knopp, T, März, T, Möddel, M, Storath, M and Weber, A (2018). Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging. Inverse Problems. 34
Beier, T (2018). Multicut Algorithms for Neurite Segmentation. Heidelberg University
Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, Köthe, U and Hamprecht, F A (2018). The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11208 LNCS 571–587. http://arxiv.org/abs/1904.12654
Wolf, S, Pape, C, Bailoni, A, Rahaman, N, Kreshuk, A, Köthe, U and Hamprecht, F A (2018). The Mutex Watershed: Efficient, Parameter-Free Image Partitioning. ECCV. Proceedings. Springer. 571-587
Rahaman, N, Arpit, D, Baratin, A, Draxler, F, Lin, M, Hamprecht, F A, Bengio, Y and Courville, A (2018). On the spectral bias of deep neural networks. arXiv preprint arXiv:1806.08734

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