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.

本文提出了一种名为Oblique-MERF的方法，在处理倾斜航拍照片重建3D场景时，通过引入一个创新的自适应占用平面和一个平滑正则化项来解决独特的数据特征，从而超越当前最先进的实时方法，降低VRAM使用量约40％并在大多数视点上实现更高的渲染帧率和更逼真的渲染效果。

Oblique-MERF: 对倾斜摄影进行重访和改进的MERF