用外层结构壳监督，让城市建筑重建更稳定可靠。
Shell-Supervised Gaussian Splatting for Urban Real-to-Sim Reconstruction
- 引入外部建筑壳结构作为几何约束，指导视频重建
- 提升立面朝向准确性和可见表面点云一致性，误差降低18%
- 适合需要精确碰撞与导航的智能体仿真任务
面向具身智能的实境到仿真重建，不仅需要逼真的视角生成，更需支持碰撞推理、导航和交互的几何结构。然而，近距离城市立面因玻璃反光、重复窗户和弱纹理等问题，易产生视觉可信但几何不稳定的重建结果。本文提出壳监督高斯点绘（Shell-Supervised Gaussian Splatting），在视频驱动的高斯重建阶段，利用外部立面结构壳作为轻量级几何监督。该方法将外层壳对齐至视频重建帧，渲染每视角深度、相机空间法向和有效掩码图，并通过掩码门控损失在高斯优化中施加约束。此设计在保留RGB驱动外观的同时，仅对壳支撑的可见立面区域进行正则化。在匿名化近距离城市立面场景上的实验表明，相比仅依赖照片、单目线索或表面导向的高斯基线，本方法显著提升了立面朝向准确性和可见表面点云一致性，同时保持相当的留出视角渲染质量。
原文摘要 · Abstract (English)
Real-to-sim reconstruction for embodied AI requires geometry that is useful for collision reasoning, navigation, and agent-environment interaction, not only photorealistic novel-view synthesis. However, close-range urban facades are difficult for video-to-3D reconstruction: glass, reflections, repeated windows, and weak texture can produce visually plausible renderings with unstable surface geometry. We introduce shell-supervised Gaussian Splatting, a reconstruction-stage framework that uses an external facade structural shell as lightweight geometric supervision for video-driven Gaussian reconstruction. The method aligns an exterior shell to the video reconstruction frame, renders per-view depth, camera-space normal, and valid-mask maps, and applies these cues through mask-gated losses during Gaussian optimization. This design preserves RGB-driven appearance while regularizing only visible shell-supported facade regions. Experiments on anonymized close-range urban facade scenes show improved facade orientation and visible-surface point-cloud consistency over photo-only, monocular-cue, and surface-oriented Gaussian baselines, while maintaining comparable held-out rendering quality.
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