Elevating 3D Models: High-Quality Texture and Geometry Refinement from a Low-Quality Model
Abstract
Elevate3D enhances both texture and geometry of low-quality 3D assets using HFS-SDEdit and monocular geometry predictors, achieving superior refinement quality.
High-quality 3D assets are essential for various applications in computer graphics and 3D vision but remain scarce due to significant acquisition costs. To address this shortage, we introduce Elevate3D, a novel framework that transforms readily accessible low-quality 3D assets into higher quality. At the core of Elevate3D is HFS-SDEdit, a specialized texture enhancement method that significantly improves texture quality while preserving the appearance and geometry while fixing its degradations. Furthermore, Elevate3D operates in a view-by-view manner, alternating between texture and geometry refinement. Unlike previous methods that have largely overlooked geometry refinement, our framework leverages geometric cues from images refined with HFS-SDEdit by employing state-of-the-art monocular geometry predictors. This approach ensures detailed and accurate geometry that aligns seamlessly with the enhanced texture. Elevate3D outperforms recent competitors by achieving state-of-the-art quality in 3D model refinement, effectively addressing the scarcity of high-quality open-source 3D assets.
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Project Page: https://cg.postech.ac.kr/research/Elevate3D/
Code: https://github.com/ryunuri/Elevate3D
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