Self-Aligning Depth-regularized Radiance Fields for Asynchronous RGB-D Sequences

arXiv:2211.07459v2 Announce Type: replace
Abstract: It has been shown that learning radiance fields with depth rendering and depth supervision can effectively promote the quality and convergence of view synthesis. However, this paradigm requires input RGB-D sequences to be synchronized, hindering its usage in the UAV city modeling scenario. As there exists asynchrony between RGB images and depth images due to high-speed flight, we propose a novel time-pose function, which is an implicit network that maps timestamps to $\rm SE(3)$ elements. …

abstract arxiv asynchronous city convergence cs.cv cs.ro fields however modeling paradigm promote quality rendering rgb-d supervision synthesis type usage view