Non-Rigid 3D Shape Correspondences: From Foundations to Open Challenges and Opportunities

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dc.contributor.authorZhuravlev, Aleksei
dc.contributor.authorBastian, Lennart
dc.contributor.authorCao, Dongliang
dc.contributor.authorEl Amrani, Nafie
dc.contributor.authorRoetzer, Paul
dc.contributor.authorEhm, Viktoria
dc.contributor.authorMarin, Riccardo
dc.contributor.authorNishizawa, Hiroki
dc.contributor.authorMorishima, Shigeo
dc.contributor.authorTheobalt, Christian
dc.contributor.authorNavab, Nassir
dc.contributor.authorCremers, Daniel
dc.contributor.authorBernard, Florian
dc.contributor.authorLähner, Zorah
dc.contributor.authorGolyanik, Vladislav
dc.contributor.editorBönsch, Andrea
dc.contributor.editorUmetani, Nobuyuki
dc.date.accessioned2026-04-16T11:53:48Z
dc.date.available2026-04-16T11:53:48Z
dc.date.issued2026
dc.description.abstractEstimating correspondences between deformed shape instances is a long-standing problem in computer graphics; numerous applications, from texture transfer to statistical modelling, rely on recovering an accurate correspondence map. Many methods have thus been proposed to tackle this challenging problem from varying perspectives, depending on the downstream application. This state-of-the-art report is geared towards researchers, practitioners, and students seeking to understand recent trends and advances in the field. We categorise developments into three paradigms: spectral methods based on functional maps, combinatorial formulations that impose discrete constraints, and deformation-based methods that directly recover a global alignment. Each school of thought offers different advantages and disadvantages, which we discuss throughout the report. Meanwhile, we highlight the latest developments in each area and suggest new potential research directions. Finally, we provide an overview of emerging challenges and opportunities in this growing field, including the recent use of vision foundation models for zero-shot correspondence and the particularly challenging task of matching partial shapes.
dc.description.number2
dc.description.sectionheadersState of the Art Reports
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume45
dc.identifier.doi10.1111/cgf.70397
dc.identifier.issn1467-8659
dc.identifier.pages35 pages
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf70397
dc.identifier.urihttps://doi.org/10.1111/cgf.70397
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.
dc.rightsCC-BY-4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectShape analysis
dc.subjectMesh geometry models
dc.subjectNeural networks
dc.titleNon-Rigid 3D Shape Correspondences: From Foundations to Open Challenges and Opportunities
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