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dc.contributor.authorRen, Jing
dc.contributor.authorMelzi, Simone
dc.contributor.authorOvsjanikov, Maks
dc.contributor.authorWonka, Peter
dc.date.accessioned2020-12-20T08:44:09Z
dc.date.available2020-12-01T11:41:25Z
dc.date.available2020-12-20T08:44:09Z
dc.date.issued2020-11-26
dc.identifier.citationRen, J., Melzi, S., Ovsjanikov, M., & Wonka, P. (2020). MapTree. ACM Transactions on Graphics, 39(6), 1–17. doi:10.1145/3414685.3417800
dc.identifier.issn1557-7368
dc.identifier.issn0730-0301
dc.identifier.doi10.1145/3414685.3417800
dc.identifier.urihttp://hdl.handle.net/10754/666191
dc.description.abstractIn this paper we propose an approach for computing multiple high-quality near-isometric dense correspondences between a pair of 3D shapes. Our method is fully automatic and does not rely on user-provided landmarks or descriptors. This allows us to analyze the full space of maps and extract multiple diverse and accurate solutions, rather than optimizing for a single optimal correspondence as done in most previous approaches. To achieve this, we propose a compact tree structure based on the spectral map representation for encoding and enumerating possible rough initializations, and a novel efficient approach for refining them to dense pointwise maps. This leads to a new method capable of both producing multiple high-quality correspondences across shapes and revealing the symmetry structure of a shape without a priori information. In addition, we demonstrate through extensive experiments that our method is robust and results in more accurate correspondences than state-of-the-art for shape matching and symmetry detection.
dc.description.sponsorshipThe authors would like to thank the anonymous reviewers for their valuable comments and helpful suggestions. Parts of this work were supported by the KAUST OSR Award No. CRG-2017-3426, and the ERC Starting Grant No. 758800 (EXPROTEA).
dc.publisherAssociation for Computing Machinery (ACM)
dc.relation.urlhttps://dl.acm.org/doi/10.1145/3414685.3417800
dc.rightsPermission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro"t or commercial advantage and that copies bear this notice and the full citation on the "rst page. Copyrights for third-party components of this work must be honored.
dc.titleMapTree: Recovering multiple solutions in the space of maps
dc.typeArticle
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalACM Transactions on Graphics
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionLIX, École Polytechnique
dc.identifier.volume39
dc.identifier.issue6
dc.identifier.pages1-17
dc.identifier.arxivid2006.02532
kaust.personRen, Jing
kaust.grant.numberCRG-2017-3426
dc.identifier.eid2-s2.0-85097350639
refterms.dateFOA2020-12-01T11:44:19Z
kaust.acknowledged.supportUnitOSR


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