Neural implicit fields have established a new paradigm for scene representation, with subsequent work achieving high-quality real-time rendering. However, reconstructing 3D scenes from oblique aerial photography presents unique challenges, such as varying spatial scale distributions and a constrained range of tilt angles, often resulting in high memory consumption and reduced rendering quality at extrapolated viewpoints. In this paper, we enhance MERF to accommodate these data characteristics by introducing an innovative adaptive occupancy plane optimized during the volume rendering process and a smoothness regularization term for view-dependent color to address these issues. Our approach, termed Oblique-MERF, surpasses state-of-the-art real-time methods by approximately 0.7 dB, reduces VRAM usage by about 40%, and achieves higher rendering frame rates with more realistic rendering outcomes across most viewpoints.

翻译：神经隐式场为场景表示建立了新范式，后续工作实现了高质量实时渲染。然而，从倾斜航空摄影中重建三维场景面临独特挑战，例如空间尺度分布变化和倾斜角度范围受限，这往往导致高内存消耗以及外推视角的渲染质量下降。本文通过引入在体渲染过程中优化的创新自适应占用平面，以及针对视角相关颜色的平滑正则化项，增强MERF以适应这些数据特征。我们的方法称为Oblique-MERF，在大多数视角下超越当前最先进的实时方法约0.7 dB，VRAM使用减少约40%，并实现了更高的渲染帧率和更逼真的渲染结果。