<scp>FRONTISPIECE</scp>. Enabling neural radiance fields for large‐scale aerial images – From a geometric reconstruction perspective

Enabling neural radiance fields for large-scale aerial images -From a geometric reconstruction perspectiveThe paper in this issue proposes a multi-camera tiling approach to perform 3D reconstruction using a neural radiance field (MCT-NeRF), which delivers superior reconstruction results for complex objects.This figure visually compares the MCT-NeRF method with other traditional reconstruction methods.The rows correspond to complex and thin objects with widths of only a few pixels in the image: (1) a stone pillar (7-11 pixels in width), (2) a light bulb (4-5 pixels lateral resolution), (3-4) a thin-frame structured arched door (each frame bar takes only 2-3 pixels in width), and (5) a group of thin pillars (2-3 pixels in width) with heavy occlusions.Our MCT-NeRF consistently outperforms the other methods in reconstructing these fine structures.For more details see Xu and Qin