LATITUDE: Robotic Global Localization with Truncated Dynamic Low-pass Filter in City-scale NeRF. (arXiv:2209.08498v1 [cs.CV])

Neural Radiance Fields (NeRFs) have made great success in representing
complex 3D scenes with high-resolution details and efficient memory.
Nevertheless, current NeRF-based pose estimators have no initial pose
prediction and are prone to local optima during optimization. In this paper, we
present LATITUDE: Global Localization with Truncated Dynamic Low-pass Filter,
which introduces a two-stage localization mechanism in city-scale NeRF. In
place recognition stage, we train a regressor through images generated from
trained NeRFs, which provides an initial value for global …

arxiv city global latitude localization nerf scale