Publications
Conference Paper
Michel, F, Kirillov, A, Brachmann, E, Krull, A, Gumhold, S, Savchynskyy, B and Rother, C (2017).
Global hypothesis generation for 6D object pose estimation.
Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.
2017-Janua 115–124.
http://arxiv.org/abs/1612.02287 Kirillov, A, Savchynskyy, B, Schlesinger, D, Vetrov, D and Rother, C (2015).
Inferring M-best diverse labelings in a single one.
Proceedings of the IEEE International Conference on Computer Vision.
2015 Inter 1814–1822
Kirillov, A, Levinkov, E, Andres, B, Savchynskyy, B and Rother, C (2017).
InstanceCut: From edges to instances with MultiCut.
Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.
2017-Janua 7322–7331
Tourani, S, Shekhovtsov, A, Rother, C and Savchynskyy, B (2018).
MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
11208 LNCS 264–281
Kappes, J Hendrik, Swoboda, P, Savchynskyy, B, Hazan, T and Schnörr, C (2015).
Probabilistic correlation clustering and image partitioning using perturbed Multicuts.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
9087 231–242
Conference Proceedings
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) Journal Article
Kappes, J H, 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 (2015).
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
International Journal of Computer Vision.
115 155–184.
http://hci.iwr.uni-heidelberg.de/opengm2/ Kappes, J H, 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 (2015).
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
International Journal of Computer Vision.
115 155–184
Kappes, J H, 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 (2015).
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
International Journal of Computer Vision.
115 155–184
Kappes, J H, 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 (2014).
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems.
CoRR.
abs/1404.0533.
http://hci.iwr.uni-heidelberg.de/opengm2/ Technical Report (3.32 MB) Arnab, A, Zheng, S, Jayasumana, S, Romera-paredes, B, Kirillov, A, Savchynskyy, B, Rother, C, Kahl, F and Torr, P (2018).
Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation.
Cvpr.
XX 1–15.
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.308.8889&rep=rep1&type=pdf%0Ahttp://dx.doi.org/10.1109/CVPR.2012.6248050 Savchynskyy, B (2019).
Discrete Graphical Models — An Optimization Perspective.
Foundations and Trends® in Computer Graphics and Vision. Now Publishers.
11 160–429