One-to-many Reconstruction of 3D Geometry of cultural Artifacts using a synthetically trained Generative Model

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dc.contributor.authorPöllabauer, Thomasen_US
dc.contributor.authorKühn, Juliusen_US
dc.contributor.authorLi, Jiayien_US
dc.contributor.authorKuijper, Arjanen_US
dc.contributor.editorBucciero, Albertoen_US
dc.contributor.editorFanini, Brunoen_US
dc.contributor.editorGraf, Holgeren_US
dc.contributor.editorPescarin, Sofiaen_US
dc.contributor.editorRizvic, Selmaen_US
dc.date.accessioned2023-09-02T07:44:29Z
dc.date.available2023-09-02T07:44:29Z
dc.date.issued2023
dc.description.abstractEstimating the 3D shape of an object using a single image is a difficult problem. Modern approaches achieve good results for general objects, based on real photographs, but worse results on less expressive representations such as historic sketches. Our automated approach generates a variety of detailed 3D representation from a single sketch, depicting a medieval statue, and can be guided by multi-modal inputs, such as text prompts. It relies solely on synthetic data for training, making it adoptable even in cases of only small numbers of training examples. Our solution allows domain experts such as a curators to interactively reconstruct potential appearances of lost artifacts.en_US
dc.description.sectionheadersAI and 3D Reconstruction III
dc.description.seriesinformationEurographics Workshop on Graphics and Cultural Heritage
dc.identifier.doi10.2312/gch.20231161
dc.identifier.isbn978-3-03868-217-2
dc.identifier.issn2312-6124
dc.identifier.pages81-84
dc.identifier.pages4 pages
dc.identifier.urihttps://doi.org/10.2312/gch.20231161
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/gch20231161
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Reconstruction; Supervised learning; Applied computing → Archaeology
dc.subjectComputing methodologies → Reconstruction
dc.subjectSupervised learning
dc.subjectApplied computing → Archaeology
dc.titleOne-to-many Reconstruction of 3D Geometry of cultural Artifacts using a synthetically trained Generative Modelen_US
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GCH 2023 - Eurographics Workshop on Graphics and Cultural Heritage