Uni-IR: One Stage is Enough for Ambiguity-Reduced Inverse Rendering

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dc.contributor.authorGe, Wenhangen_US
dc.contributor.authorFeng, Jiaweien_US
dc.contributor.authorShen, Guibaoen_US
dc.contributor.authorChen, Ying-Congen_US
dc.contributor.editorChristie, Marcen_US
dc.contributor.editorHan, Ping-Hsuanen_US
dc.contributor.editorLin, Shih-Syunen_US
dc.contributor.editorPietroni, Nicoen_US
dc.contributor.editorSchneider, Teseoen_US
dc.contributor.editorTsai, Hsin-Rueyen_US
dc.contributor.editorWang, Yu-Shuenen_US
dc.contributor.editorZhang, Eugeneen_US
dc.date.accessioned2025-10-07T06:04:40Z
dc.date.available2025-10-07T06:04:40Z
dc.date.issued2025
dc.description.abstractInverse rendering aims to decompose an image into geometry, materials, and lighting. Recently, Neural Radiance Fields (NeRF) based inverse rendering has significantly advanced, bridging the gap between NeRF-based models and conventional rendering engines. Existing methods typically adopt a two-stage optimization approach, beginning with volume rendering for geometry reconstruction, followed by physically based rendering (PBR) for materials and lighting estimation. However, the inherent ambiguity between materials and lighting during PBR, along with the suboptimal nature of geometry reconstruction by volume rendering, compromises the outcomes. To address these challenges, we introduce Uni-IR, a unified framework that imposes mutual constraints to alleviate ambiguity by integrating volume rendering and physically based rendering. Specifically, we employ a physically-based volume rendering (PBVR) approach that incorporates PBR concepts into volume rendering, directly facilitating connections with materials and lighting, in addition to geometry. Both rendering methods are utilized simultaneously during optimization, imposing mutual constraints and optimizing geometry, materials, and lighting synergistically. By employing a carefully designed unified representation for both lighting and materials, Uni-IR achieves high-quality geometry reconstruction, materials, and lighting estimation across various object types.en_US
dc.description.sectionheadersRendering & Inverse Rendering
dc.description.seriesinformationPacific Graphics Conference Papers, Posters, and Demos
dc.identifier.doi10.2312/pg.20251295
dc.identifier.isbn978-3-03868-295-0
dc.identifier.pages11 pages
dc.identifier.urihttps://doi.org/10.2312/pg.20251295
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/pg20251295
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 → 3D imaging; Reconstruction
dc.subjectComputing methodologies → 3D imaging
dc.subjectReconstruction
dc.titleUni-IR: One Stage is Enough for Ambiguity-Reduced Inverse Renderingen_US
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