PNeRFLoc: Visual Localization with Point-Based Neural Radiance Fields
Boming Zhao,
Luwei Yang,
Mao Mao
et al.
Abstract:Due to the ability to synthesize high-quality novel views, Neural Radiance Fields (NeRF) has been recently exploited to improve visual localization in a known environment. However, the existing methods mostly utilize NeRF for data augmentation to improve the regression model training, and their performances on novel viewpoints and appearances are still limited due to the lack of geometric constraints. In this paper, we propose a novel visual localization framework, i.e., PNeRFLoc, based on a unified point-base… Show more
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