SiZeUp：基于深度序数损失的航拍图像快速3D代理模型构建方法
SiZeUp: Fast 3D Proxy from Aerial Images via Depth Ordinal Loss
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中文总结 AI 辅助
SiZeUp是一种从校准倾斜航拍图像构建大规模城市3D代理模型的方法，采用“ footprint 高度”表示法与深度序数一致性损失，实现23-52倍加速，适用于大规模城市建模。
中文摘要 AI 辅助
我们提出SiZeUp，一种直接从校准倾斜航拍图像构建大规模城市3D代理模型的快速且可扩展的方法。该方法采用“ footprint 高度”表示法，将3D建筑物抽象简化为低维优化问题，其中建筑物 footprint 通过单一高度参数进行拉伸。为实现高效且鲁棒的高度估计，我们引入深度序数一致性损失，该损失强制渲染代理的相对深度排序与单目深度模型预测的深度先验保持一致。这通过可微渲染器实现，该渲染器将参数化建筑物代理映射为多视图深度图像，使梯度能够从深度监督传播至建筑物高度。我们的序数公式在实践中产生稳定的优化，且避免了显式特征匹配或密集点云重建。与单目尺度歧义下可能不可靠的度量深度不同，我们的深度序数一致性损失基于相对深度操作，提供跨视图更可靠的信号。结合高效动态视图选择，我们的方法比最先进的代理重建管道实现了23-52倍的加速，同时保持了可比的代理级覆盖率和体积一致性，使其非常适合大规模城市建模任务。
英文摘要
We present SiZeUp, a fast and scalable approach for constructing large-scale 3D urban proxy models directly from calibrated oblique aerial imagery. Our method adopts a height-from-footprint representation, reducing 3D building abstraction to a low-dimensional optimization problem in which building footprints are extruded by a single height parameter. To enable efficient and robust height estimation, we introduce an ordinal depth consistency loss that enforces agreement between the relative depth ordering of rendered proxies and depth priors predicted by a monocular depth model. This is realized through a differentiable renderer that maps parametric building proxies into multi-view depth images, allowing gradients to be propagated from depth supervision to building heights. Our ordinal formulation produces stable optimization in practice and avoids explicit feature matching or dense point cloud reconstruction. Rather than relying on metric depth, which can be unreliable under monocular scale ambiguity, our ordinal depth consistency loss operates on relative depths, providing a more reliable signal across views. Combined with an efficient dynamic view selection, our approach achieves a 23-52$\times$ speedup over state-of-the-art proxy reconstruction pipelines while maintaining comparable proxy-level coverage and volume consistency, making it well suited for large-scale urban modeling tasks.
发表机构
- Shenzhen University（深圳大学）
- Simon Fraser University（西蒙菲莎大学）
机构由 AI 辅助整理，请以论文原文为准。
