% generated by bibtexbrowser % % Encoding: UTF-8 @article{rodola-ijcv12-2, author = {E. Rodola and A. Albarelli and F. Bergamasco and A. Torsello}, title = {A Scale Independent Selection Process for 3D Object Recognition in Cluttered Scenes}, journal = {International Journal of Computer Vision}, volume = {102}, number = {1}, pages = {129--145}, titleurl = {rodola-ijcv12-2.pdf}, month = {mar}, year = {2013}, doi = {10.1007/s11263-012-0568-x}, publisher = {Springer US}, keywords = {Shape Analysis, Recognition, Geometry Processing}, } @article{albarelli-pr15, author = {A. Albarelli and E. Rodola and A. Torsello}, title = {Fast and Accurate Surface Alignment through an Isometry-Enforcing Game}, journal = {Pattern Recognition}, year = {2015}, volume = {48}, issue = {7}, pages = {2209--2226}, doi = {10.1016/j.patcog.2015.01.020}, publisher = {Elsevier}, keywords = {Shape Analysis, Correspondence, Geometry Processing}, } @inproceedings{rodola-cvpr12, author = {E. Rodola and A.M. Bronstein and A. Albarelli and F. Bergamasco and A. Torsello}, title = {A game-theoretic approach to deformable shape matching}, pages = {182-189}, doi = {10.1109/CVPR.2012.6247674}, issn = {1063-6919}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2012}, titleurl = {rodola-cvpr12.pdf}, keywords = {Shape Analysis}, } @inproceedings{rodola-3dimpvt11-2, author = {A. Albarelli and E. Rodola and A. Torsello}, title = {A Non-Cooperative Game for 3D Object Recognition in Cluttered Scenes}, booktitle = {International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)}, year = {2011}, pages = {252-259}, doi = {10.1109/3DIMPVT.2011.39}, titleurl = {rodola-3dimpvt11-2.pdf}, keywords = {Shape Analysis, Recognition, Correspondence, Segmentation}, } @inproceedings{rodola-3dimpvt11-1, author = {A. Torsello and E. Rodola and A. Albarelli}, title = {Sampling Relevant Points for Surface Registration}, booktitle = {International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)}, year = {2011}, pages = {290-295}, doi = {10.1109/3DIMPVT.2011.43}, titleurl = {rodola-3dimpvt11-1.pdf}, keywords = {Shape Analysis}, } @inproceedings{rodola-cvpr10, author = {A. Albarelli and E. Rodola and A. Torsello}, title = {A Game-Theoretic Approach to Fine Surface Registration without Initial Motion Estimation}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, pages = {430-437}, issn = {1063-6919}, doi = {10.1109/CVPR.2010.5540183}, year = {2010}, titleurl = {rodola-cvpr10.pdf}, keywords = {Shape Analysis, Correspondence}, } @inproceedings{Schmidt-Cremers-dagm09, author = {F. R. Schmidt and D. Cremers}, title = {A Closed-Form Solution for Image Sequence Segmentation with Dynamical Shape Priors}, booktitle = {Pattern Recognition (Proc. DAGM)}, year = {2009}, address = {Jena, Germany}, month = {September}, titleurl = {sc09.pdf}, topic = {Shape Priors}, keywords = {shape-priors}, } @inproceedings{Schmidt-et-al-cvpr09, author = {F. R. Schmidt and E. Toeppe and D. Cremers}, title = {Efficient Planar Graph Cuts with Applications in Computer Vision}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2009}, address = {Miami, Florida}, month = {jun}, titleurl = {schmidt_et_al_cvpr09.pdf}, award = {Received a CVPR Doctoral Spotlight Award}, topic = {Shape Analysis}, keywords = {shape-analysis}, pages = {351-356}, } @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{Schoenemann-Cremers-07a, author = {T. Schoenemann and D. Cremers}, title = {Globally Optimal Image Segmentation with an Elastic Shape Prior}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, year = {2007}, address = {Rio de Janeiro, Brazil}, month = {oct}, keywords = {shape-priors}, titleurl = {shape_iccv07.pdf}, topic = {Shape, Segmentation, Graph, Shape Priors}, } @inproceedings{SFC-07, author = {F. R. Schmidt and D Farin and D. Cremers}, title = {Fast Matching of Planar Shapes in Sub-cubic Runtime}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, year = {2007}, address = {Rio de Janeiro, Brazil}, month = {oct}, keywords = {shape-analysis}, titleurl = {SFC-07.pdf}, topic = {Shape Analysis}, } @inproceedings{STCB-07a, author = {F. R. Schmidt and E. Toeppe and D. Cremers and Y. Boykov}, title = {Intrinsic Mean for Semimetrical Shape Retrieval via Graph Cuts}, booktitle = {Pattern Recognition (Proc. DAGM)}, year = {2007}, series = {LNCS}, volume = {4713}, pages = {446--455}, address = {Heidelberg, Germany}, month = {sep}, publisher = {Springer}, keywords = {shape-analysis}, titleurl = {STCB-07a.pdf}, topic = {Shape Analysis}, copyright = {{Springer-Verlag Berlin Heidelberg 2007}}, } @inproceedings{STCB-07, author = {F. R. Schmidt and E. Toeppe and D. Cremers and Y. Boykov}, title = {Efficient Shape Matching via Graph Cuts}, booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, year = {2007}, series = {LNCS}, volume = {4679}, pages = {39--54}, address = {Ezhou, China}, month = {aug}, publisher = {Springer}, keywords = {shape-analysis}, titleurl = {STCB-07.pdf}, topic = {Shape Analysis}, copyright = {{Springer-Verlag Berlin Heidelberg 2007}}, } @inproceedings{Cremers07, author = {D. Cremers}, title = {Nonlinear Dynamical Shape Priors for Level Set Segmentation}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2007}, titleurl = {cremers_cvpr07.pdf}, keywords = {shape-priors}, topic = {Level Sets, Tracking, Shape Priors, Segmentation}, } @article{Cremers-jsc08, author = {D. Cremers}, title = {Nonlinear Dynamical Shape Priors for Level Set Segmentation}, journal = {Journal of Scientific Computing}, volume = {35}, number = {2-3}, pages = {132--143}, year = {2008}, month = {jun}, titleurl = {cremers_jsc08.pdf}, keywords = {shape-priors}, topic = {Level Sets, Tracking, Shape Priors, Segmentation}, } @incollection{Cremers-11, author = {D. Cremers}, title = {Image Segmentation with Shape Priors: Explicit Versus Implicit Representations}, booktitle = {Handbook of Mathematical Methods in Imaging}, publisher = {Springer}, year = {2011}, pages = {1453-1487}, titleurl = {cremers_handbook2011.pdf}, keywords = {shape, segmentation}, topic = {Shape}, } @inproceedings{FRS-et-al-06, author = {F. R. Schmidt and M. Clausen and D. Cremers}, title = {Shape Matching by Variational Computation of Geodesics on a Manifold}, booktitle = {Pattern Recognition (Proc. DAGM)}, year = {2006}, series = {LNCS}, volume = {4174}, pages = {142--151}, address = {Berlin, Germany}, month = {sep}, publisher = {Springer}, keywords = {shape-analysis}, titleurl = {FRS-et-al-06.pdf}, topic = {Shape Analysis}, copyright = {{Springer-Verlag Berlin Heidelberg 2006}}, } @inproceedings{BBPW04, author = {T. Brox and A. Bruhn and N. Papenberg and J. Weickert}, title = {High accuracy optical flow estimation based on a theory for warping}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2004}, editor = {T. Pajdla and J. Matas}, volume = {3024}, series = {LNCS}, pages = {25--36}, address = {Prague, Czech Republic}, month = {may}, publisher = {Springer}, award = {{Received "The Longuet-Higgins Best Paper Award"}}, copyright = {{Springer-Verlag Berlin Heidelberg 2004}}, titleurl = {brox_eccv04_of.pdf}, keywords = {shape-priors, optical-flow}, topic = {Optic Flow, Motion}, } @article{Cremers-06, author = {D. Cremers}, title = {Dynamical statistical shape priors for level set based tracking}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, year = {2006}, volume = {28}, number = {8}, pages = {1262--1273}, month = {aug}, keywords = {shape-priors}, titleurl = {cremers_pami06.pdf}, topic = {Level Sets, Shape Priors, Segmentation, Tracking}, } @article{Brox-et-al-pami09, author = {T. Brox and B. Rosenhahn and J. Gall and D. Cremers}, title = {Combined region- and motion-based 3D tracking of rigid and articulated objects}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, year = {2009}, volume = {32}, number = {3}, pages = {402-415}, keywords = {tracking,shape-priors}, titleurl = {brox_et_al_pami09.pdf}, topic = {Level Sets, Shape Priors, 3DTracking}, } @inproceedings{Cremers-Grady-06, author = {D. Cremers and L. Grady}, title = {Statistical priors for combinatorial optimization: efficient solutions via {G}raph {C}uts}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2006}, editor = {A. Leonardis and H. Bischof and A. Pinz}, volume = {3953}, series = {LNCS}, pages = {263--274}, address = {Graz, Austria}, month = {may}, publisher = {Springer}, copyright = {{Springer-Verlag Berlin Heidelberg 2006}}, keywords = {image-segmentation,shape,Parzen,parametric,2d cardiac ultrasound,3d ct prostate}, titleurl = {cremers_grady_eccv06.pdf}, topic = {Statistics, Texture}, } @article{Cremers-et-al-ijcv07, author = {D. Cremers and M. Rousson and R. Deriche}, title = {A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape}, journal = {International Journal of Computer Vision}, year = {2007}, volume = {72}, number = {2}, pages = {195--215}, month = {apr}, titleurl = {cremers_rousson_deriche_ijcv07.pdf}, keywords = {shape-priors, medical imaging}, topic = {Segmentation, Statistics, Shape Priors, Level Sets, Motion}, } @inproceedings{Cremers-et-al-02, author = {D. Cremers and T. Kohlberger and C. Schnörr}, title = {Nonlinear shape statistics in {M}umford--{S}hah based segmentation}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2002}, editor = {A. Heyden and others}, volume = {2351}, series = {LNCS}, pages = {93--108}, address = {Copenhagen}, month = {May}, publisher = {Springer}, titleurl = {cremers_eccv02.pdf}, keywords = {shape-priors}, topic = {Segmentation, Statistics, Shape Priors, Machine Learning}, } @article{Cremers-et-al-03hd, author = {D. Cremers and T. Kohlberger and C. Schnörr}, title = {Shape {S}tatistics in {K}ernel {S}pace for {V}ariational {I}mage {S}egmentation}, journal = {Pattern {R}ecognition}, year = {2003}, volume = {36}, pages = {1929--1943}, number = {9}, award = {Awarded Best Paper of the Year 2003}, titleurl = {nonlinear_pr03.pdf}, keywords = {shape-priors}, topic = {Shape Priors, Statistics, Machine Learning, Segmentation}, } @inproceedings{Cremers-Funkalea-05, author = {D. Cremers and G. Funka-Lea}, title = {Dynamical statistical shape priors for level set based tracking}, booktitle = {Intl. {W}orkshop on {V}ariational and {L}evel {S}et {M}ethods}, year = {2005}, editor = {N. Paragios and F. Faugeras and T. Chan and C. Schn{\"o}rr}, volume = {3752}, series = {LNCS}, publisher = {Springer}, keywords = {dynamical shape priors}, titleurl = {cremers_funkalea_05.pdf}, topic = {Shape Priors, Statistics, Dynamical Systems, Segmentation, Tracking}, } @inproceedings{Cremers-et-al-04b, author = {D. Cremers and S. J. Osher and S. Soatto}, title = {Kernel density estimation and intrinsic alignment for knowledge-driven segmentation: {T}eaching level sets to walk}, booktitle = {Pattern Recognition (Proc. DAGM)}, year = {2004}, editor = {C. E. Rasmussen}, volume = {3175}, series = {LNCS}, pages = {36--44}, publisher = {Springer}, titleurl = {cremers_dagm04.pdf}, keywords = {shape-priors}, topic = {Level Sets, Shape Priors, Statistics, Segmentation}, } @incollection{Cremers-Rousson-07, author = {D. Cremers and M. Rousson}, title = {Efficient kernel density estimation of shape and intensity priors for level set segmentation}, booktitle = {Parametric and {G}eometric {D}eformable {M}odels: {A}n application in {B}iomaterials and {M}edical {I}magery}, publisher = {Springer}, year = {2007}, editor = {J. S. Suri and A. Farag}, month = {May}, titleurl = {cremers_rousson07.pdf}, topic = {Segmentation, Shape Priors, Medical Image Analysis, Statistics}, keywords = {shape-priors, medical imaging}, } @inproceedings{Cremers-et-al-dyn, author = {D. Cremers and C. Schnörr and J. Weickert and C. Schellewald}, title = {Learning of translation invariant shape knowledge for steering diffusion snakes}, booktitle = {Dynamische {P}erzeption}, year = {2000}, editor = {G. Baratoff and H. Neumann}, volume = {9}, series = {Proceedings on Artificial Intelligence}, pages = {117--122}, address = {Ulm Germany}, month = {Nov.}, publisher = {Infix}, titleurl = {dynperz00.ps.gz}, keywords = {shape-priors}, topic = {Shape Priors, Statistics, Segmentation}, } @inproceedings{Cremers-et-al-00, author = {D. Cremers and C. Schnörr and J. Weickert and C. Schellewald}, title = {Diffusion {S}nakes using statistical shape knowledge}, booktitle = {Algebraic {F}rames for the {P}erception-{A}ction {C}ycle}, year = {2000}, editor = {G. Sommer and Y.Y. Zeevi}, volume = {1888}, series = {LNCS}, pages = {164--174}, address = {Kiel, Germany}, month = {Sept.}, publisher = {Springer}, titleurl = {afpac2000.ps.gz}, keywords = {shape-priors}, topic = {Shape Priors, Statistics, Segmentation}, } @inproceedings{Cremers-Soatto-03b, author = {D. Cremers and S. Soatto}, title = {A pseudo-distance for shape priors in level set segmentation}, booktitle = {I{EEE} 2nd {I}nt. {W}orkshop on {V}ariational, {G}eometric and {L}evel {S}et {M}ethods}, year = {2003}, editor = {N. Paragios}, pages = {169--176}, address = {Nice}, titleurl = {cremers_soatto_vlsm03.pdf}, keywords = {shape-priors}, topic = {Shape Priors}, } @inproceedings{Cremers-et-al-03, author = {D. Cremers and N. Sochen and C. Schnörr}, title = {Towards {R}ecognition-based {V}ariational {S}egmentation {U}sing {S}hape {P}riors and {D}ynamic {L}abeling}, booktitle = {Scale-{S}pace {M}ethods in {C}omputer {V}ision}, year = {2003}, editor = {L. D. Griffin and M. Lillholm}, volume = {2695}, series = {LNCS}, pages = {388--400}, address = {Isle of Skye}, publisher = {Springer}, titleurl = {dynamic_labeling.pdf}, keywords = {shape-priors}, topic = {Shape Priors, Level Sets, Segmentation, Recognition}, } @inproceedings{Cremers-et-al-04, author = {D. Cremers and N. Sochen and C. Schnörr}, title = {Multiphase dynamic labeling for variational recognition-driven image segmentation}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2004}, editor = {T. Pajdla and V. Hlavac}, volume = {3024}, series = {LNCS}, pages = {74--86}, publisher = {Springer}, titleurl = {cremers_eccv04.pdf}, keywords = {shape-priors}, topic = {Shape Priors, Level Sets, Segmentation, Recognition}, } @article{Cremers-et-al-02c, author = {D. Cremers and F. Tischhäuser and J. Weickert and C. Schnörr}, title = {Diffusion {S}nakes: {I}ntroducing statistical shape knowledge into the {M}umford--{S}hah functional}, journal = {International Journal of Computer Vision}, year = {2002}, volume = {50}, pages = {295--313}, number = {3}, titleurl = {cremers_et_al_ijcv02.pdf}, keywords = {shape-priors}, topic = {Shape Priors, Segmentation, Statistics}, } @article{Manay-et-al-06, author = {S. Manay and D. Cremers and B.-W. Hong and A. Yezzi and S. Soatto}, title = {Integral invariants for shape matching}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, year = {2006}, month = {oct}, volume = {28}, number = {10}, pages = {1602--1618}, keywords = {shape}, topic = {Shape, Correspondence}, titleurl = {manay_et_al_pami06.pdf}, } @inproceedings{Manay-et-al-05, author = {S. Manay and D. Cremers and A. J. Yezzi and S. Soatto}, title = {One-shot integral invariant shape priors for variational segmentation}, booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, volume = {3757}, editor = {A. Rangarajan and B. Vemuri and A. L. Yuille}, series = {LNCS}, year = {2005}, pages = {414--426}, keywords = {image-segmentation,shape,Dijkstra + PDE}, topic = {Segmentation, Shape, Correspondence}, } @inproceedings{Rousson-Cremers-05, author = {M. Rousson and D. Cremers}, title = {Efficient kernel density estimation of shape and intensity priors for level set segmentation}, booktitle = {Medical Image Computing and Computer Assisted Intervention (MICCAI)}, year = {2005}, volume = {1}, pages = {757--764}, keywords = {image-segmentation,shape,Parzen,parametric,2d cardiac ultrasound,3d ct prostate, medical imaging}, titleurl = {rousson_cremers05.pdf}, topic = {Shape, Segmentation, Statistics, Level Sets}, } @inproceedings{Kohlberger-et-al-06, author = {T. Kohlberger and D. Cremers and M. Rousson and R. Ramaraj}, title = {4D shape priors for level set segmentation of the left myocardium in {SPECT} sequences}, booktitle = {Medical Image Computing and Computer Assisted Intervention (MICCAI)}, volume = {4190}, series = {LNCS}, pages = {92--100}, year = {2006}, month = {oct}, keywords = {image-segmentation,shape,Parzen,parametric,2d cardiac ultrasound,3d ct prostate, medical imaging}, titleurl = {kohlberger_et_al_miccai06.pdf}, topic = {Shape, Segmentation, Medical Image Analysis, Level Sets}, } @inproceedings{andres-et-al-cvpr08, author = {B. Andres and C. Nieuwenhuis and D. Kondermann and U. Köthe and R. Hamprecht}, title = {On Errors-In-Variables Regression with Arbitrary Covariance and its Application to Optical Flow Estimation}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2008}, address = {Anchorage, Alaska}, month = {jun}, pages = {1--6}, keywords = {Shape Priors}, titleurl = {andres-et-al-cvpr08.pdf}, } @inproceedings{aubry-et-al-4dmod11, author = {M. Aubry and U. Schlickewei and D. Cremers}, title = {The Wave Kernel Signature: A Quantum Mechanical Approach To Shape Analysis}, booktitle = {I{EEE} {I}nternational {C}onference on {C}omputer {V}ision ({ICCV}) - {W}orkshop on {D}ynamic {S}hape {C}apture and {A}nalysis ({4DMOD})}, year = {2011}, titleurl = {compute_WKS.m}, keywords = {Shape Analysis}, topic = {Shape Analysis}, } @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{Stuehmer-Cremers-emmcvpr15, author = {J. Stühmer and D. Cremers}, title = {A Fast Projection Method for Connectivity Constraints in Image Segmentation}, booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR)}, editor = {X.-C. Tai and E. Bae and T. F. Chan and M. Lysaker}, series = {LNCS}, year = {2015}, keywords = {image-segmentation,constrained convex optimization,shape-priors,medical imaging}, topic = {Segmentation, Shape Priors}, } @inproceedings{LRSBC16, author = {Z. Lähner and E. Rodola and F. R. Schmidt and M. M. Bronstein and D. Cremers}, title = {Efficient Globally Optimal 2D-to-3D Deformable Shape Matching}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {May}, year = {2016}, keywords = {Shape Analysis, Geometry Processing}, url = {http://vision.in.tum.de/~laehner/Elastic2D3D/}, } @inproceedings{SHREC16-3dor, title = {SHREC’16: Matching of Deformable Shapes with Topological Noise}, author = {Z. Lähner and E. Rodola and M. M. Bronstein and D. Cremers and O. Burghard and L. Cosmo and A. Dieckmann and R. Klein and Y. Sahillioglu}, booktitle = {Proc. of Eurographics Workshop on 3D Object Retrieval (3DOR)}, year = {2016}, month = {May}, topic = {Shape Analysis}, url = {http://vision.in.tum.de/~laehner/shrec2016/}, keywords = {Shape Analysis, Shape Matching, SHREC, Topology, Geometry Processing}, } @inproceedings{shrec16-partial, title = {SHREC’16: Partial Matching of Deformable Shapes}, author = {L. Cosmo and E. Rodola and M. M. Bronstein and A. Torsello and D. Cremers and Y. Sahillioglu}, booktitle = {Proc. of Eurographics Workshop on 3D Object Retrieval (3DOR)}, year = {2016}, month = {May}, keywords = {Shape Analysis, Shape Matching, SHREC}, } @inproceedings{kernel17, author = {M. Vestner and Z. Lähner and A. Boyarski and O. Litany and R. Slossberg and T. Remez and E. Rodolà and A. M. Bronstein and M. M. Bronstein and R. Kimmel and D. Cremers}, title = {Efficient Deformable Shape Correspondence via Kernel Matching}, booktitle = {International Conference on 3D Vision (3DV)}, year = {2017}, month = {October}, address = {Qingdao, China}, award = {Oral Presentation}, keywords = {Shape Analysis, Shape Matching, Geometry Processing}, } @inproceedings{wang2020directshape, author = {R. Wang and N. Yang and J. Stueckler and D. Cremers}, title = {DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation}, booktitle = {Proc. of the IEEE International Conference on Robotics and Automation (ICRA)}, year = {2020}, keywords = {stereo, 3D reconstruction, semantic SLAM, 3D object detection, scene understanding, direct shape}, } @inproceedings{eisenberger2020hamiltonian, author = {M. Eisenberger and D. Cremers}, title = {Hamiltonian Dynamics for Real-World Shape Interpolation}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2020}, award = {Spotlight Presentation}, keywords = {Shape Analysis, Geometry Processing}, } @inproceedings{holzschuh20simanneal, author = {B Holzschuh and Z Lähner and D Cremers}, title = {Simulated Annealing for 3D Shape Correspondence}, booktitle = {International Conference on 3D Vision (3DV)}, year = {2020}, award = {Oral Presentation}, keywords = {Shape Analysis, Shape Matching, Geometry Processing}, } @inproceedings{aygun20heatkernel, author = {M Aygün and Z Lähner and D Cremers}, title = {Unsupervised Dense Shape Correspondence using Heat Kernels}, booktitle = {International Conference on 3D Vision (3DV)}, year = {2020}, keywords = {Shape Analysis, Shape Matching, Geometry Processing}, } @inproceedings{gao2021multi, title = {Isometric Multi-Shape Matching}, author = {M Gao and Z Lähner and J Thunberg and D Cremers and F Bernard}, year = {2021}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, keywords = {Shape Analysis, Geometry Processing, Shape Correspondence, Multi Shape Matching}, award = {Oral Presentation}, } @inproceedings{koestler2022intrinsic, author = {L Koestler and D Grittner and M Moeller and D Cremers and Z Lähner}, title = {Intrinsic Neural Fields: Learning Functions on Manifolds}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2022}, eprint = {2203.07967}, eprinttype = {arXiv}, keywords = {Neural Fields, Shape Analysis, Geometry Processing}, } @inproceedings{gao2023sigma, author = {M Gao and P Roetzer and M Eisenberger and Z Lähner and M Moeller and D Cremers and F Bernard}, title = { {SIGMA}: Quantum Scale-Invariant Global Sparse Shape Matching}, booktitle = {International Conference on Computer Vision (ICCV)}, year = {2023}, keywords = {Shape Analysis, Geometry Processing, Global Optimisation, Mixed-Integer Programming, Laplace-Betrami}, } @inproceedings{weber2024finslerlaplacebeltrami, title = {Finsler-Laplace-Beltrami Operators with Application to Shape Analysis}, author = {S Weber and T Dages and M Gao and D Cremers}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, keywords = {shape analysis, finsler manifold}, titleurl = {weber_finsler.png}, year = {2024}, eprint = {2404.03999}, eprinttype = {arXiv}, eprintclass = {cs.CV}, }