Recent Trends in 3D Reconstruction of General Non-Rigid Scenes

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dc.contributor.authorYunus, Razaen_US
dc.contributor.authorLenssen, Jan Ericen_US
dc.contributor.authorNiemeyer, Michaelen_US
dc.contributor.authorLiao, Yiyien_US
dc.contributor.authorRupprecht, Christianen_US
dc.contributor.authorTheobalt, Christianen_US
dc.contributor.authorPons-Moll, Gerarden_US
dc.contributor.authorHuang, Jia-Binen_US
dc.contributor.authorGolyanik, Vladislaven_US
dc.contributor.authorIlg, Eddyen_US
dc.contributor.editorAristidou, Andreasen_US
dc.contributor.editorMacdonnell, Rachelen_US
dc.date.accessioned2024-04-30T09:03:05Z
dc.date.available2024-04-30T09:03:05Z
dc.date.issued2024
dc.description.abstractReconstructing models of the real world, including 3D geometry, appearance, and motion of real scenes, is essential for computer graphics and computer vision. It enables the synthesizing of photorealistic novel views, useful for the movie industry and AR/VR applications. It also facilitates the content creation necessary in computer games and AR/VR by avoiding laborious manual design processes. Further, such models are fundamental for intelligent computing systems that need to interpret real-world scenes and actions to act and interact safely with the human world. Notably, the world surrounding us is dynamic, and reconstructing models of dynamic, non-rigidly moving scenes is a severely underconstrained and challenging problem. This state-of-the-art report (STAR) offers the reader a comprehensive summary of state-of-the-art techniques with monocular and multi-view inputs such as data from RGB and RGB-D sensors, among others, conveying an understanding of different approaches, their potential applications, and promising further research directions. The report covers 3D reconstruction of general non-rigid scenes and further addresses the techniques for scene decomposition, editing and controlling, and generalizable and generative modeling. More specifically, we first review the common and fundamental concepts necessary to understand and navigate the field and then discuss the state-of-the-art techniques by reviewing recent approaches that use traditional and machine-learning-based neural representations, including a discussion on the newly enabled applications. The STAR is concluded with a discussion of the remaining limitations and open challenges.en_US
dc.description.documenttypestar
dc.description.number2
dc.description.sectionheadersState of the Art Reports
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume43
dc.identifier.doi10.1111/cgf.15062
dc.identifier.issn1467-8659
dc.identifier.pages42 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.15062
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15062
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Reconstruction; Volumetric models; Point-based models; Mesh geometry models; Motion capture; Shape representations; Appearance and texture representations
dc.subjectComputing methodologies → Reconstruction
dc.subjectVolumetric models
dc.subjectPoint
dc.subjectbased models
dc.subjectMesh geometry models
dc.subjectMotion capture
dc.subjectShape representations
dc.subjectAppearance and texture representations
dc.titleRecent Trends in 3D Reconstruction of General Non-Rigid Scenesen_US
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