A Convex Relaxation Approach for Computing Minimal Partitions

Thomas Pock, Chambolle Antonin, Daniel Cremers, Horst Bischof

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '09)
Publisher.
Pages810-817
Publication statusPublished - 2009
EventIEEE Conference on Computer Vision and Pattern Recognition (CVPR '09) - Miami Beach, Florida, United States
Duration: 20 Jun 200925 Jun 2009

Conference

ConferenceIEEE Conference on Computer Vision and Pattern Recognition (CVPR '09)
CountryUnited States
CityMiami Beach, Florida
Period20/06/0925/06/09

Cite this

Pock, T., Antonin, C., Cremers, D., & Bischof, H. (2009). A Convex Relaxation Approach for Computing Minimal Partitions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '09) (pp. 810-817). ..

A Convex Relaxation Approach for Computing Minimal Partitions. / Pock, Thomas; Antonin, Chambolle; Cremers, Daniel; Bischof, Horst.

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '09). ., 2009. p. 810-817.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Pock, T, Antonin, C, Cremers, D & Bischof, H 2009, A Convex Relaxation Approach for Computing Minimal Partitions. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '09). ., pp. 810-817, IEEE Conference on Computer Vision and Pattern Recognition (CVPR '09), Miami Beach, Florida, United States, 20/06/09.
Pock T, Antonin C, Cremers D, Bischof H. A Convex Relaxation Approach for Computing Minimal Partitions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '09). . 2009. p. 810-817
Pock, Thomas ; Antonin, Chambolle ; Cremers, Daniel ; Bischof, Horst. / A Convex Relaxation Approach for Computing Minimal Partitions. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '09). ., 2009. pp. 810-817
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