Publications
2020
Schnörr, (2020).
Assignment Flows.
Handbook of Variational Methods for Nonlinear Geometric Data. Springer. 235—260.
https://www.springer.com/gp/book/9783030313500 Kluger, F, Brachmann, E, Ackermann, H, Rother, C, Yang, M Ying and Rosenhahn, B (2020).
CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus.
CVPR 2020.
http://arxiv.org/abs/2001.02643 PDF (9.95 MB) Bollweg, S, Haußmann, M, Kasieczka, G, Luchmann, M, Plehn, T and Thompson, J (2020).
Deep-Learning Jets with Uncertainties and More.
SciPost Phys.
8.
https://scipost.org/10.21468/SciPostPhys.8.1.006 Technical Report (1.65 MB) Haller, S, Prakash, M, Hutschenreiter, L, Pietzsch, T, Rother, C, Jug, F, Swoboda, P and Savchynskyy, B (2020).
A Primal-Dual Solver for Large-Scale Tracking-by-Assignment.
AISTATS 2020 PDF (1.04 MB) Roth, K, Milbich, T, Sinha, S, Gupta, P, Ommer, B and Cohen, J Paul (2020).
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning.
International Conference on Machine Learning (ICML).
https://arxiv.org/pdf/2002.08473.pdf Mustikovela, S K, Jampani, V, De Mello, S, Liu, S, Iqbal, U, Rother, C and Kautz, J (2020).
Self-Supervised Viewpoint Learning From Image Collections.
CONSAC.
https://github.com/NVlabs/SSV PDF (8.77 MB) 2019
Schnörr, (2019).
Assignment Flows.
Variational Methods for Nonlinear Geometric Data and Applications. Springer
Bendinger, A L, Debus, C, Glowa, C, Karger, C P, Peter, J and Storath, M (2019).
Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models, in press.
Physics in Medicine and Biology.
64 Mackowiak, R, Lenz, P, Ghori, O, Diego, F, Lange, O and Rother, C (2019).
CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation.
British Machine Vision Conference 2018, BMVC 2018 Li, W, Hosseini Jafari, O and Rother, C (2019).
Deep Object Co-segmentation.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
11363 LNCS 638–653
Savchynskyy, B (2019).
Discrete Graphical Models — An Optimization Perspective.
Foundations and Trends® in Computer Graphics and Vision. Now Publishers.
11 160–429
Abu Alhaija, H, Mustikovela, S Karthik, Geiger, A and Rother, C (2019).
Geometric Image Synthesis.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
11366 LNCS 85–100.
https://youtu.be/W2tFCz9xJoU Pages