Mesh Draping: Parametrization‐Free Neural Mesh Transfer

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dc.contributor.authorHertz, A.en_US
dc.contributor.authorPerel, O.en_US
dc.contributor.authorGiryes, R.en_US
dc.contributor.authorSorkine‐Hornung, O.en_US
dc.contributor.authorCohen‐Or, D.en_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2023-03-22T15:07:12Z
dc.date.available2023-03-22T15:07:12Z
dc.date.issued2023
dc.description.abstractDespite recent advances in geometric modelling, 3D mesh modelling still involves a considerable amount of manual labour by experts. In this paper, we introduce Mesh Draping: a neural method for transferring existing mesh structure from one shape to another. The method drapes the source mesh over the target geometry and at the same time seeks to preserve the carefully designed characteristics of the source mesh. At its core, our method deforms the source mesh using progressive positional encoding (PE). We show that by leveraging gradually increasing frequencies to guide the neural optimization, we are able to achieve stable and high‐quality mesh transfer. Our approach is simple and requires little user guidance, compared to contemporary surface mapping techniques which rely on parametrization or careful manual tuning. Most importantly, Mesh Draping is a parameterization‐free method, and thus applicable to a variety of target shape representations, including point clouds, polygon soups and non‐manifold meshes. We demonstrate that the transferred meshing remains faithful to the source mesh design characteristics, and at the same time fits the target geometry well.en_US
dc.description.number1
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14721
dc.identifier.issn1467-8659
dc.identifier.pages72-85
dc.identifier.urihttps://doi.org/10.1111/cgf.14721
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14721
dc.publisherEurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.rightsCC BY-NC Attribution-NonCommercial 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectshape synthesis
dc.subjectshape modelling
dc.subjectneural networks
dc.titleMesh Draping: Parametrization‐Free Neural Mesh Transferen_US
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