Elevating 3D Models: High-Quality Texture and Geometry Refinement from a Low-Quality Model

Fig. 1. 3D refinement examples from (a) a degraded real-world scan [Downs et al. 2022] and (c) a state-of-the-art image-to-3D generative model [Xiang et al. 2024]. Our method, Elevate3D, effectively refines both texture and geometry while preserving their alignment, as shown in (b) and (d). Inputs for the experiment: the GSO dataset [Downs et al. 2022], and ©MasaStojanovic/pixabay.

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, Ele-vate3D 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.