  The insertion of objects into a scene and relighting are commonly utilized
applications in augmented reality (AR). Previous methods focused on inserting
virtual objects using CAD models or real objects from single-view images,
resulting in highly limited AR application scenarios. We propose a novel
NeRF-based pipeline for inserting object NeRFs into scene NeRFs, enabling novel
view synthesis and realistic relighting, supporting physical interactions like
casting shadows onto each other, from two sets of images depicting the object
and scene. The lighting environment is in a hybrid representation of Spherical
Harmonics and Spherical Gaussians, representing both high- and low-frequency
lighting components very well, and supporting non-Lambertian surfaces.
Specifically, we leverage the benefits of volume rendering and introduce an
innovative approach for efficient shadow rendering by comparing the depth maps
between the camera view and the light source view and generating vivid soft
shadows. The proposed method achieves realistic relighting effects in extensive
experimental evaluations.
