Multi-Level Neural Scene Graphs for Scalable Reconstruction of Dynamic Urban Environments

We propose a multi-level neural scene graph representation that scales to large geographic areas with dozens of vehicle captures and hundreds of dynamic objects, enabling efficient training and rendering of radiance fields for dynamic urban environments.