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dc.contributor.authorSundt, Peder Bergebakken
dc.contributor.authorTheoharis, Theoharis
dc.date.accessioned2023-12-05T09:00:47Z
dc.date.available2023-12-05T09:00:47Z
dc.date.created2023-09-05T12:05:31Z
dc.date.issued2023
dc.identifier.citationComputers & graphics. 2023, 115 122-136.en_US
dc.identifier.issn0097-8493
dc.identifier.urihttps://hdl.handle.net/11250/3105940
dc.description.abstractWe propose Medial Atom Ray Fields (MARFs), a novel neural object representation that enables accurate differentiable surface rendering with a single network evaluation per camera ray. Existing neural ray fields struggle with multi-view consistency and representing surface discontinuities. MARFs address both using a medial shape representation, a dual representation of solid geometry that yields cheap geometrically grounded surface normals, in turn enabling computing analytical curvature despite the network having no second derivative. MARFs map a camera ray to multiple medial intersection candidates, subject to ray-sphere intersection testing. We illustrate how the learned medial shape quantities applies to sub-surface scattering, part segmentation, and aid representing a space of articulated shapes. Able to learn a space of shape priors, MARFs may prove useful for tasks like shape retrieval and shape completion, among others. Code and data can be found at https://github.com/pbsds/MARF.en_US
dc.language.isoengen_US
dc.publisherElsevier B. V.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleMARF: The Medial Atom Ray Field object representationen_US
dc.title.alternativeMARF: The Medial Atom Ray Field object representationen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber122-136en_US
dc.source.volume115en_US
dc.source.journalComputers & graphicsen_US
dc.identifier.doi10.1016/j.cag.2023.06.032
dc.identifier.cristin2172485
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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