天空坠落-GS – 从卫星图像合成沉浸式3D城市场景
Skyfall-GS – Synthesizing Immersive 3D Urban Scenes from Satellite Imagery

原始链接: https://skyfall-gs.jayinnn.dev/

合成大规模、可探索且几何精确的3D城市场景是一项具有挑战性但有价值的任务,可为沉浸式和具身应用提供支持。 挑战在于缺乏用于训练泛化生成模型的大规模和高质量的真实世界3D扫描数据。 在本文中,我们采取了一种替代方法,通过协同利用现成的卫星图像(提供逼真的粗略几何形状)和开放域扩散模型(用于创建高质量的近景外观)来创建大规模3D场景。 我们提出了Skyfall-GS,这是第一个无需昂贵3D标注即可实现街区级3D场景创建框架,并具有实时、沉浸式3D探索功能。 我们定制了一种由课程驱动的迭代细化策略,以逐步增强几何完整性和照片级真实纹理。 大量实验表明,与最先进的方法相比,Skyfall-GS提供了改进的跨视图一致性几何形状和更逼真的纹理。

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原文

Synthesizing large-scale, explorable, and geometrically accurate 3D urban scenes is a challenging yet valuable task in providing immersive and embodied applications. The challenges lie in the lack of large-scale and high-quality real-world 3D scans for training generalizable generative models. In this paper, we take an alternative route to create large-scale 3D scenes by synergizing the readily available satellite imagery that supplies realistic coarse geometry and the open-domain diffusion model for creating high-quality close-up appearances. We propose Skyfall-GS, the first city-block scale 3D scene creation framework without costly 3D annotations, also featuring real-time, immersive 3D exploration. We tailor a curriculum-driven iterative refinement strategy to progressively enhance geometric completeness and photorealistic textures. Extensive experiments demonstrate that Skyfall-GS provides improved cross-view consistent geometry and more realistic textures compared to state-of-the-art approaches.

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