% generated by bibtexbrowser % % Encoding: UTF-8 @inproceedings{Toeppe-et-al-accv10, author = {E. Toeppe and M. R. Oswald and D. Cremers and C. Rother}, title = {Image-based 3D Modeling via Cheeger Sets}, booktitle = {Asian Conference on Computer Vision}, year = {2010}, address = {Queenstown, New Zealand}, month = {nov}, titleurl = {toeppe_et_al_accv10.pdf}, award = {Received Honorable Mention Award}, topic = {Single View Reconstruction, Convex Relaxation Methods}, pages = {53-64}, keywords = {singleview, convex-relaxation}, } @article{Cremers-Kolev-pami11, author = {D. Cremers and K. Kolev}, title = {Multiview Stereo and Silhouette Consistency via Convex Functionals over Convex Domains}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, year = {2011}, volume = {33}, number = {6}, pages = {1161--1174}, titleurl = {cremers_kolev_pami11.pdf}, topic = {3D Reconstruction}, keywords = {3d-reconstruction, convex-relaxation, 3drec}, } @article{Pock-et-al-10, author = {T. Pock and D. Cremers and H. Bischof and A. Chambolle}, title = {Global Solutions of Variational Models with Convex Regularization}, journal = {SIAM Journal on Imaging Sciences}, year = {2010}, volume = {3}, number = {4}, pages = {1122--1145}, titleurl = {pock_et_al_siims10.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @inproceedings{KPC-10, author = {K. Kolev and T. Pock and D. Cremers}, title = {Anisotropic Minimal Surfaces Integrating Photoconsistency and Normal Information for Multiview Stereo}, optcrossref = {}, optkey = {}, booktitle = {European Conference on Computer Vision (ECCV)}, optpages = {}, year = {2010}, opteditor = {}, optvolume = {}, optnumber = {}, optseries = {}, address = {Heraklion, Greece}, month = {September}, optorganization = {}, optpublisher = {}, optannote = {}, titleurl = {KPC-10.pdf}, topic = {3D Reconstruction, Convex Relaxation Methods}, keywords = {3d-reconstruction,3drec, convex-relaxation}, } @inproceedings{Oswald-et-al-dagm09, author = {M. R. Oswald and E. Toeppe and K. Kolev and D. Cremers}, title = {Non-Parametric Single View Reconstruction of Curved Objects using Convex Optimization}, booktitle = {Pattern Recognition (Proc. DAGM)}, year = {2009}, address = {Jena, Germany}, month = {September}, titleurl = {otkc_dagm09.pdf}, award = {Received a DAGM Paper Award}, topic = {Single View Reconstruction, Convex Relaxation Methods}, pages = {171-180}, keywords = {singleview, convex-relaxation}, } @inproceedings{Pock2008_Convex, author = {T. Pock and T. Schoenemann and G. Graber and H. Bischof and D. Cremers}, title = {A Convex Formulation of Continuous Multi-Label Problems}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2008}, address = {Marseille, France}, month = {October}, titleurl = {pock_et_al_eccv08.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @inproceedings{Pock-et-al-09, author = {T. Pock and A. Chambolle and H. Bischof and D. Cremers}, title = {A Convex Relaxation Approach for Computing Minimal Partitions}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2009}, address = {Miami, Florida}, titleurl = {pock_et_al_cvpr09.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation, medical imaging}, } @article{Chambolle-et-al-siims12, author = {A. Chambolle and D. Cremers and T. Pock}, title = {A Convex Approach to Minimal Partitions}, journal = {SIAM Journal on Imaging Sciences}, year = {2012}, volume = {5}, number = {4}, pages = {1113--1158}, titleurl = {Chambolle_et_al_siims12.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @inproceedings{Kolev-Cremers-09, author = {K. Kolev and D. Cremers}, title = {Continuous Ratio Optimization via Convex Relaxation with Applications to Multiview 3D Reconstruction}, optcrossref = {}, optkey = {}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, optpages = {}, year = {2009}, opteditor = {}, optvolume = {}, optnumber = {}, optseries = {}, address = {Miami, Florida}, titleurl = {Kolev-Cremers-09.pdf}, topic = {3D Reconstruction}, keywords = {3d-reconstruction, convex-relaxation}, } @inproceedings{Trobin2008_Fusion, author = {W. Trobin and T. Pock and D. Cremers and H. Bischof}, title = {Continuous Energy Minimization via Repeated Binary Fusion}, optcrossref = {}, optkey = {}, booktitle = {European Conference on Computer Vision (ECCV)}, optpages = {}, year = {2008}, opteditor = {}, optvolume = {}, optnumber = {}, optseries = {}, address = {Marseille, France}, month = {October}, optorganization = {}, optpublisher = {}, optannote = {}, titleurl = {trobin_eccv2008.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @inproceedings{KC-08, author = {K. Kolev and D. Cremers}, title = {Integration of Multiview Stereo and Silhouettes via Convex Functionals on Convex Domains}, optcrossref = {}, optkey = {}, booktitle = {European Conference on Computer Vision (ECCV)}, optpages = {}, year = {2008}, opteditor = {}, optvolume = {}, optnumber = {}, optseries = {}, address = {Marseille, France}, month = {October}, optorganization = {}, optpublisher = {}, optannote = {}, titleurl = {KC-08.pdf}, topic = {3D Reconstruction}, keywords = {3d-reconstruction, convex-relaxation}, } @inproceedings{KSKSC-08, author = {M. Klodt and T. Schoenemann and K. Kolev and M. Schikora and D. Cremers}, title = {An Experimental Comparison of Discrete and Continuous Shape Optimization Methods}, year = {2008}, address = {Marseille, France}, month = {October}, booktitle = {European Conference on Computer Vision (ECCV)}, titleurl = {KSKSC-08.pdf}, topic = {3D Reconstruction, Convex Relaxation Methods}, keywords = {3d-reconstruction, convex-relaxation}, } @inproceedings{Cremers-et-al-cvpr08, author = {D. Cremers and F. R. Schmidt and F. Barthel}, title = {Shape Priors in Variational Image Segmentation: Convexity, Lipschitz Continuity and Globally Optimal Solutions}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2008}, address = {Anchorage, Alaska}, month = {jun}, keywords = {shape-priors, convex-relaxation}, titleurl = {cremers_et_al_cvpr08.pdf}, topic = {Shape Priors, Convex Relaxation Methods}, } @inproceedings{KKBC-07, author = {K. Kolev and M. Klodt and T. Brox and D. Cremers}, title = {Propagated Photoconsistency and Convexity in Variational Multiview 3D Reconstruction}, booktitle = {Workshop on Photometric Analysis for Computer Vision}, year = {2007}, address = {Rio de Janeiro, Brazil}, month = {oct}, titleurl = {KKBC-07.pdf}, topic = {3D Reconstruction}, keywords = {3d-reconstruction, convex-relaxation}, } @inproceedings{KKBEC-07, author = {K. Kolev and M. Klodt and T. Brox and S. Esedoglu and D. Cremers}, title = {Continuous Global Optimization in Multiview 3D Reconstruction}, booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, year = {2007}, series = {LNCS}, volume = {4679}, pages = {441--452}, address = {Ezhou, China}, month = {aug}, publisher = {Springer}, titleurl = {KKBEC-07.pdf}, topic = {3D Reconstruction}, copyright = {{Springer-Verlag Berlin Heidelberg 2007}}, keywords = {3d-reconstruction, convex-relaxation}, } @techreport{CCP_08, author = {A. Chambolle and D. Cremers and T. Pock}, title = {A Convex Approach for Computing Minimal Partitions}, institution = {Dept. of Computer Science, University of Bonn}, type = {Technical report}, number = {TR-2008-05}, address = {Bonn, Germany}, month = {nov}, titleurl = {minimal_partitions_08.pdf}, year = {2008}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @incollection{Cremers-et-al-11, author = {D. Cremers and T. Pock and K. Kolev and A. Chambolle}, title = {Convex Relaxation Techniques for Segmentation, Stereo and Multiview Reconstruction}, booktitle = {Markov Random Fields for Vision and Image Processing}, publisher = {MIT Press}, year = {2011}, titleurl = {cremers_et_al_mrf2011.pdf}, keywords = {3d-reconstruction, convex-relaxation}, topic = {Convex Relaxation Methods}, } @incollection{Klodt-et-al-13, author = {M. Klodt and F. Steinbruecker and D. Cremers}, title = {Moment Constraints in Convex Optimization for Segmentation and Tracking}, booktitle = {Advanced Topics in Computer Vision}, publisher = {Springer}, year = {2013}, titleurl = {Klodt-et-al-13.pdf}, keywords = {segmentation, convex-relaxation, medical imaging}, topic = {Convex Relaxation Methods, Segmentation}, } @article{Goldluecke-et-al-ijcv14, author = {B. Goldluecke and M. Aubry and K. Kolev and D. Cremers}, title = {A Super-resolution Framework for High-Accuracy Multiview Reconstruction}, journal = {International Journal of Computer Vision}, year = {2014}, month = {jan}, volume = {106}, number = {2}, pages = {172-191}, keywords = {convex-relaxation}, titleurl = {goldluecke-et-al-ijcv14.pdf}, } @inproceedings{Keuchel-et-al-02, author = {J. Keuchel and C. Schnoerr and C. Schellewald and D. Cremers}, title = {Unsupervised Image Partitioning with Semidefinite Programmifng}, booktitle = {Pattern Recognition}, editor = {van Gool, L.}, publisher = {Springer}, series = {LNCS}, volume = {2449}, year = {2002}, titleurl = {keuchel_et_al_02.pdf}, address = {Z{\"u}rich}, month = {Sept.}, pages = {141--149}, keywords = {convex-relaxation}, } @article{Kolev-et-al-ijcv09, author = {K. Kolev and M. Klodt and T. Brox and D. Cremers}, title = {Continuous Global Optimization in Multiview 3D Reconstruction}, journal = {International Journal of Computer Vision}, year = {2009}, month = {August}, volume = {84}, number = {1}, pages = {80--96}, titleurl = {Kolev-et-al-ijcv09.pdf}, topic = {3D Reconstruction, Convex Relaxation Methods}, keywords = {3d-reconstruction,3drec,convex-relaxation}, } @inproceedings{Keuchel-et-al-01, author = {J. Keuchel and C. Schellewald and D. Cremers and C. Schnoerr}, title = {Convex Relaxations for Binary Image Partitioning and Perceptual Grouping}, booktitle = {Pattern Recognition}, editor = {Radig, B. and Florczyk, S.}, publisher = {Springer}, series = {LNCS}, volume = {2191}, year = {2001}, award = {Received a DAGM Paper Award}, address = {Munich, Germany}, month = {Sept.}, pages = {353--360}, keywords = {convex-relaxation}, } @article{Cremers-12, author = {D. Cremers}, title = {Optimal Solutions for Semantic Image Decomposition}, journal = {Image and Vision Computing}, year = {2012}, volume = {30}, pages = {476--477}, number = {8}, titleurl = {cremers_ivc12.pdf}, keywords = {convex-relaxation, segmentation}, } @article{Keuchel-et-al-03, author = {J. Keuchel and C. Schnörr and C. Schellewald and D. Cremers}, title = {Binary partitioning, perceptual grouping, and restoration with semidefinite programming}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, year = {2003}, volume = {25}, pages = {1364--1379}, number = {11}, keywords = {convex-relaxation}, titleurl = {keuchel_et_al_pami03.pdf}, } @article{GSC12:siims, author = {B. Goldluecke and E. Strekalovskiy and D. Cremers}, title = {The Natural Total Variation Which Arises from Geometric Measure Theory}, journal = {SIAM Journal on Imaging Sciences}, year = {2012}, volume = {5}, number = {2}, pages = {537–-563}, titleurl = {GSC12_siims.pdf}, topic = {Convex Relaxation Methods, Optic Flow}, keywords = {convex-relaxation, optical-flow}, } @inproceedings{Pock-et-al-iccv09, author = {T. Pock and D. Cremers and H. Bischof and A. Chambolle}, title = {An Algorithm for Minimizing the Piecewise Smooth Mumford-Shah Functional}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, year = {2009}, address = {Kyoto, Japan}, titleurl = {pock_et_al_iccv09.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @inproceedings{GC10:ML, title = {Convex Relaxation for Multilabel Problems with Product Label Spaces}, booktitle = {European Conference on Computer Vision (ECCV)}, author = {B. Goldluecke and D. Cremers}, year = {2010}, titleurl = {GC10_ML.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @techreport{souiai_tr_13, author = {M. Souiai and E. Strekalovskiy and C. Nieuwenhuis and D. Cremers}, title = {Label Configuration Priors for Continuous Multi-Label Optimization}, type = {Technical report}, school = {Computer Vision Group, TU Munich}, titleurl = {souiai_tr_13.pdf}, year = {2013}, topic = {Convex Relaxation Methods,Image Segmentation}, keywords = {convex-relaxation,label configuration priors,medical imaging}, } @inproceedings{Strekalovskiy-Cremers-cvpr11, author = {E. Strekalovskiy and D. Cremers}, title = {Total Variation for Cyclic Structures: Convex Relaxation and Efficient Minimization}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2011}, address = {Colorado Springs, Colorado}, month = {jun}, titleurl = {strekalovskiy_cremers_cvpr11.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @inproceedings{GC11:iccv, author = {B. Goldluecke and D. Cremers}, title = {Introducing Total Curvature for Image Processing}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, year = {2011}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, titleurl = {GC11_iccv.pdf}, } @inproceedings{SGC11:iccv, author = {E. Strekalovskiy and B. Goldluecke and D. Cremers}, title = {Tight Convex Relaxations for Vector-Valued Labeling Problems}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, year = {2011}, titleurl = {sgc11_iccv.pdf}, topic = {Convex Relaxation Methods, Optic Flow}, keywords = {convex-relaxation,optical-flow}, } @article{Kolev_et_al_pami12, author = {K. Kolev and T. Brox and D. Cremers}, title = {Fast Joint Estimation of Silhouettes and Dense {3D} Geometry from Multiple Images}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, year = {2012}, volume = {34}, number = {3}, pages = {493--505}, titleurl = {Kolev_et_al_pami12.pdf}, topic = {3D Reconstruction}, keywords = {convex-relaxation, 3d-reconstruction}, } @inproceedings{Strekalovskiy-Cremers-iccv11, author = {E. Strekalovskiy and D. Cremers}, title = {Generalized Ordering Constraints for Multilabel Optimization}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, year = {2011}, titleurl = {strekalovskiy_cremers_iccv2011.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @inproceedings{Nieuwenhuis_emmcvpr11, author = {C. Nieuwenhuis and E. Toeppe and D. Cremers}, title = {Space-Varying Color Distributions for Interactive Multiregion Segmentation: Discrete versus Continuous Approaches}, year = {2011}, booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, topic = {segmentation, Convex Relaxation Methods}, titleurl = {nieuwenhuis_et_al_emmcvpr11.pdf}, pages = {177-190}, keywords = {segmentation, convex-relaxation}, } @inproceedings{KC11:iccv, author = {M. Klodt and D. Cremers}, title = {A Convex Framework for Image Segmentation with Moment Constraints}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, year = {2011}, titleurl = {kc11_iccv.pdf}, topic = {segmentation, Convex Relaxation Methods}, keywords = {segmentation, convex-relaxation, medical imaging}, } @phdthesis{Kolev-diss, author = {K. Kolev}, title = {Convexity in Image-Based 3D Surface Reconstruction}, school = {Department of Computer Science, Technical University Munich, Germany}, month = {January}, year = {2012}, titleurl = {Kolev-diss.pdf}, keywords = {convex-relaxation}, } @inproceedings{Toeppe-et-al-LNCS-2011, author = {E. Toeppe and M. R. Oswald and D. Cremers and C. Rother}, title = {Silhouette-Based Variational Methods for Single View Reconstruction}, booktitle = {Proceedings of the 2010 international conference on Video Processing and Computational Video}, editor = {D. Cremers and M. A. Magnor and M. R. Oswald and L. Zelnik-Manor}, year = {2011}, isbn = {978-3-642-24869-6}, location = {Dagstuhl Castle, Germany}, pages = {104--123}, numpages = {20}, publisher = {Springer-Verlag}, address = {Berlin, Heidelberg}, keywords = {convex-relaxation, convex optimization, image-based modeling, singleview}, } @inproceedings{Strekalovskiy-et-al-eccv12, author = {E. Strekalovskiy and C. Nieuwenhuis and D. Cremers}, title = {Nonmetric Priors for Continuous Multilabel Optimization}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2012}, address = {Firenze, Italy}, month = {oct}, publisher = {Springer}, topic = {Convex Relaxation Methods,Segmentation}, keywords = {convex-relaxation, Segmentation}, } @inproceedings{Oswald-et-al-cvpr12, author = {M. R. Oswald and E. Toeppe and D. Cremers}, title = {Fast and Globally Optimal Single View Reconstruction of Curved Objects}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2012}, address = {Providence, Rhode Island}, month = {jun}, titleurl = {oswald_toeppe_cremers_cvpr12.pdf}, topic = {Single View Reconstruction}, pages = {534-541}, keywords = {convex-relaxation, singleview}, } @inproceedings{Strekalovskiy-et-al-cvpr12, author = {E. Strekalovskiy and A. Chambolle and D. Cremers}, title = {A Convex Representation for the Vectorial Mumford-Shah Functional}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2012}, address = {Providence, Rhode Island}, month = {jun}, titleurl = {strekalovskiy_chambolle_cremers_cvpr12.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @article{nieuwenhuis-cremers-pami12_2, author = {C. Nieuwenhuis and D. Cremers}, title = {Spatially Varying Color Distributions for Interactive Multi-Label Segmentation}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, year = {2013}, volume = {35}, number = {5}, pages = {1234-1247}, titleurl = {nieuwenhuis-cremers-pami12_2.pdf}, topic = {Segmentation}, keywords = {convex-relaxation, segmentation, medical imaging}, } @article{nieuwenhuis-et-al-ijcv13, author = {C. Nieuwenhuis and E. Toeppe and D. Cremers}, title = {A Survey and Comparison of Discrete and Continuous Multi-label Optimization Approaches for the Potts Model}, journal = {International Journal of Computer Vision}, volume = {104}, number = {3}, pages = {223-240}, year = {2013}, month = {sep}, keywords = {convex-relaxation, Segmentation}, } @article{Cremers_Strekalovskiy_jmiv12, author = {D. Cremers and E. Strekalovskiy}, title = {Total Cyclic Variation and Generalizations}, journal = {Journal of Mathematical Imaging and Vision}, year = {2012}, month = {nov}, volume = {47}, number = {3}, pages = {258--277}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, titleurl = {Cremers_Strekalovskiy_jmiv12.pdf}, } @inproceedings{ufer_et_al_eccv12, author = {N. Ufer and M. Souiai and D. Cremers}, title = {Wehrli 2.0: An Algorithm for ”Tidying up Art”}, booktitle = {VISART “Where Computer Vision Meets Art” workshop, ECCV 2012}, year = {2012}, address = {Firenze, Italy}, month = {oct}, publisher = {Springer}, topic = {Segmentation}, keywords = {convex-relaxation, segmentation}, titleurl = {ufer_et_al_eccv12.pdf}, } @inproceedings{toeppe_et_al_cvpr13, author = {E. Toeppe and C. Nieuwenhuis and D. Cremers}, title = {Volume Constraints for Single View Reconstruction}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2013}, address = {Portland, USA}, topic = {Segmentation}, keywords = {singleview, convex-relaxation,segmentation}, titleurl = {toeppe_et_al_cvpr13.pdf}, } @article{GSC13:vml, author = {B. Goldluecke and E. Strekalovskiy and D. Cremers}, title = {Tight Convex Relaxations for Vector-Valued Labeling}, journal = {SIAM Journal on Imaging Sciences}, year = {2013}, volume = {6}, number = {3}, pages = {1626–-1664}, titleurl = {GSC13_siims.pdf}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation}, } @inproceedings{souiai-et-al-emmcvpr13, author = {M. Souiai and E. Strekalovskiy and C. Nieuwenhuis and D. Cremers}, title = {A Co-occurrence Prior for Continuous Multi-Label Optimization}, booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, year = {2013}, topic = {Convex Relaxation Methods, Segmentation}, keywords = {convex-relaxation}, } @inproceedings{stangl-et-al-13, author = {F. Stangl and M. Souiai and D. Cremers}, title = {Performance Evaluation of Narrow Band Methods for Variational Stereo}, booktitle = {35th German Conference on Pattern Recognition (GCPR)}, year = {2013}, titleurl = {stangl_et_al_gcpr13.pdf}, keywords = {convex-relaxation}, } @inproceedings{moellenhoff-et-al-13, author = {T. Möllenhoff and C. Nieuwenhuis and E. Toeppe and D. Cremers}, title = {Efficient Convex Optimization for Minimal Partition Problems with Volume Constraints}, booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, year = {2013}, titleurl = {moellenhoff_et_al_13.pdf}, keywords = {convex-relaxation}, } @inproceedings{klodt_etal_2013gcpr, author = {M. Klodt and J. Sturm and D. Cremers}, title = {Scale-Aware Object Tracking with Convex Shape Constraints on RGB-D Images}, booktitle = {German Conference on Pattern Recognition (GCPR)}, year = {2013}, address = {Saarbr\"ucken, Germany}, month = {September}, keywords = {convex-relaxation, rgb-d}, titleurl = {klodt_etal_2013gcpr.pdf}, } @inproceedings{lellmann-et-al-iccv2013, author = {J. Lellmann and E. Strekalovskiy and S. Koetter and D. Cremers}, title = {Total Variation Regularization for Functions with Values in a Manifold}, year = {2013}, address = {Sydney, Australia}, month = {December}, titleurl = {lellmann-et-al-iccv2013.pdf}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation, Segmentation}, } @inproceedings{Nieuwenhuis-et-al-iccv13, author = {C. Nieuwenhuis and E. Strekalovskiy and D. Cremers}, title = {Proportion Priors for Image Sequence Segmentation}, year = {2013}, address = {Sydney, Australia}, month = {December}, titleurl = {nieuwenhuis-et-al-iccv2013.pdf}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, topic = {Convex Relaxation Methods}, keywords = {convex-relaxation, Segmentation}, } @inproceedings{stuehmer-et-al-iccv2013, author = {J. Stühmer and P. Schröder and D. Cremers}, title = {Tree Shape Priors with Connectivity Constraints using Convex Relaxation on General Graphs}, year = {2013}, address = {Sydney, Australia}, month = {December}, titleurl = {stuehmer-et-al-iccv2013.pdf}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, topic = {Segmentation, Shape Priors}, keywords = {Convex-Relaxation, Segmentation, shape-priors, medical imaging}, award = {Oral Presentation}, } @inproceedings{Oswald-Cremers-ICCV-4DMOD-2013, author = {M. R. Oswald and D. Cremers}, title = {A Convex Relaxation Approach to Space Time Multi-view 3D Reconstruction}, booktitle = {{ICCV} {W}orkshop on {D}ynamic {S}hape {C}apture and {A}nalysis ({4DMOD})}, year = {2013}, numpages = {8}, titleurl = {oswald-cremers-ICCV-4DMOD2013.pdf}, topic = {3D Reconstruction}, keywords = {space-time, 3d-reconstruction, convex-relaxation}, } @article{strekalovskiy-et-al-siims14, author = {E. Strekalovskiy and A. Chambolle and D. Cremers}, title = {Convex Relaxation of Vectorial Problems with Coupled Regularization}, journal = {SIAM Journal on Imaging Sciences}, year = {2014}, volume = {7}, number = {1}, pages = {294--336}, topic = {Convex Relaxation Methods, Optic Flow}, keywords = {convex-relaxation, optical-flow}, } @inproceedings{Oswald-Cremers-BMVC-2014, author = {M. R. Oswald and D. Cremers}, title = {Surface Normal Integration for Convex Space-time Multi-view Reconstruction}, booktitle = {British Machine Vision Conference (BMVC)}, year = {2014}, numpages = {11}, keywords = {space-time, 3d-reconstruction, surface normals, convex-relaxation}, } @inproceedings{Nieuwenhuis-et-al-eccv14, author = {C. Nieuwenhuis and S. Hawe and M. Kleinsteuber and D. Cremers}, title = {Co-Sparse Textural Similarity for Interactive Segmentation}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2014}, titleurl = {nieuwenhuis-et-al-eccv14.pdf}, keywords = {convex-relaxation, Segmentation}, } @inproceedings{Oswald-et-al-ECCV-2014, author = {M. R. Oswald and J. Stühmer and D. Cremers}, title = {Generalized Connectivity Constraints for Spatio-temporal 3D Reconstruction}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2014}, pages = {32-46}, numpages = {14}, keywords = {connectivity constraints, space-time, 3d-reconstruction, convex-relaxation}, topic = {3D Reconstruction, Shape Priors}, } @inproceedings{Strekalovskiy-Cremers-eccv14, author = {E. Strekalovskiy and D. Cremers}, title = {Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2014}, pages = {127-141}, keywords = {convex-relaxation}, } @inproceedings{Nagaraja-et-al-iccv15, author = {N. Nagaraja and F. R. Schmidt and T. Brox}, title = {Video Segmentation with Just a Few Strokes}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, month = {Dec}, year = {2015}, address = {Santiago, Chile}, keywords = {segmentation, convex-relaxation}, } @inproceedings{moellenhoff-laude-cvpr16, author = {T. Möllenhoff and E. Laude and M. Moeller and J. Lellmann and D. Cremers}, title = {Sublabel-Accurate Relaxation of Nonconvex Energies}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2016}, titleurl = {moellenhoff_laude_cvpr_16.pdf}, keywords = {convex-relaxation}, award = {Oral Presentation, Received the Best Paper Honorable Mention Award at CVPR 2016}, } @inproceedings{laude16eccv, author = {E. Laude and T. Möllenhoff and M. Moeller and J. Lellmann and D. Cremers}, title = {Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies}, year = {2016}, month = {October}, booktitle = {European Conference on Computer Vision (ECCV)}, keywords = {convex-optimization, convex-relaxation, multilabeling, primal-dual}, } @inproceedings{moellenhoff-iccv-2017, title = {Sublabel-Accurate Discretization of Nonconvex Free-Discontinuity Problems}, author = {T. Möllenhoff and D. Cremers}, booktitle = {International Conference on Computer Vision (ICCV)}, year = {2017}, month = {October}, address = {Venice, Italy}, keywords = {convex-relaxation}, }