VF-NeRF: Viewshed Fields for Rigid NeRF Registration
Leo Segre Shai Avidan
3D scene registration is a fundamental problem in computer vision that seeks
the best 6-DoF alignment between two scenes. This problem was extensively
investigated in the case of point clouds and meshes, but there has been
relatively limited work regarding Neural Radiance Fields (NeRF). In this paper,
we consider the problem of rigid registration between two NeRFs when the
position of the original cameras is not given. Our key novelty is the
introduction of Viewshed Fields (VF), an implicit function that determines, for
each 3D point, how likely it is to be viewed by the original cameras. We
demonstrate how VF can help in the various stages of NeRF registration, with an
extensive evaluation showing that VF-NeRF achieves SOTA results on various
datasets with different capturing approaches such as LLFF and Objaverese.