3分钟完成高精度室内平面重建，无需依赖复杂检测流程。
PlanarSplatting: Accurate Planar Surface Reconstruction in 3 Minutes
- 直接对3D平面基元进行显式优化，通过平面投射生成2.5D深度与法向图。
- 在ScanNet和ScanNet++上数百个场景中实现3分钟内完成重建，精度显著提升。
- 适合需要快速高质量结构化数据的场景重建任务，代码将开源。
本文提出PlanarSplatting，一种超快且精确的多视角室内图像表面重建方法。鉴于3D平面在室内场景中具有紧凑性与结构表达力，我们构建了一个显式优化框架，通过将3D平面投影至2.5D深度图与法向图来拟合预期表面。由于直接作用于3D平面基元，该方法无需依赖2D/3D平面检测、匹配与追踪，显著简化流程。结合基于CUDA的平面投射实现，PlanarSplatting可在3分钟内完成单个室内场景重建，并展现出更优几何精度。在包含数百个场景的ScanNet和ScanNet++数据集上进行了大规模定量评估，充分验证了其优势。我们相信该方法将在未来结构化数据采集中发挥重要作用。代码将公开。项目页：https://icetttb.github.io/PlanarSplatting/
原文摘要 · Abstract (English)
This paper presents PlanarSplatting, an ultra-fast and accurate surface reconstruction approach for multiview indoor images. We take the 3D planes as the main objective due to their compactness and structural expressiveness in indoor scenes, and develop an explicit optimization framework that learns to fit the expected surface of indoor scenes by splatting the 3D planes into 2.5D depth and normal maps. As our PlanarSplatting operates directly on the 3D plane primitives, it eliminates the dependencies on 2D/3D plane detection and plane matching and tracking for planar surface reconstruction. Furthermore, the essential merits of plane-based representation plus CUDA-based implementation of planar splatting functions, PlanarSplatting reconstructs an indoor scene in 3 minutes while having significantly better geometric accuracy. Thanks to our ultra-fast reconstruction speed, the largest quantitative evaluation on the ScanNet and ScanNet++ datasets over hundreds of scenes clearly demonstrated the advantages of our method. We believe that our accurate and ultrafast planar surface reconstruction method will be applied in the structured data curation for surface reconstruction in the future. The code of our CUDA implementation will be publicly available. Project page: https://icetttb.github.io/PlanarSplatting/
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