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Publications

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Author Title Type [ Year(Asc)]
Filters: Author is Lempitsky, Victor  [Clear All Filters]
2012
Lempitsky, V, Blake, A and Rother, C (2012). Branch-and-mincut: Global optimization for image segmentation with high-level priors. Journal of Mathematical Imaging and Vision. 44 315–329
2010
Lempitsky, V, Rother, C, Roth, S and Blake, A (2010). Fusion moves for markov random field optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32 1392–1405
Lempitsky, V, Rother, C, Roth, S and Blake, A (2010). Fusion moves for markov random field optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32 1392–1405
2009
Lempitsky, V, Kohli, P, Rother, C and Sharp, T (2009). Image segmentation with a bounding box prior. Proceedings of the IEEE International Conference on Computer Vision. 277–284
2008
Lempitsky, V, Roth, S and Rother, C (2008). FusionFlow: Discrete-continuous optimization for optical flow estimation. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Lempitsky, V, Blake, A and Rother, C (2008). Image segmentation by branch-and-mincut. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5305 LNCS 15–29
Lempitsky, V, Blake, A and Rother, C (2008). Image segmentation by branch-and-mincut. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5305 LNCS 15–29
2007
Lempitsky, V, Rother, C and Blake, A (2007). LogCut - Efficient graph cut optimization for markov random fields. Proceedings of the IEEE International Conference on Computer Vision
Rother, C, Kolmogorov, V, Lempitsky, V and Szummer, M (2007). Optimizing binary MRFs via extended roof duality. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Rother, C, Kolmogorov, V, Lempitsky, V and Szummer, M (2007). Optimizing Binary MRFs via Extended Roof Duality Technical Report MSR-TR-2007-46. Computing. http://research.microsoft.com/vision/cambridge/