UncLe-SLAM: Uncertainty Learning for Dense Neural SLAM
Erik Sandström,
Kevin Ta,
Luc Van Gool
et al.
Abstract:We present an uncertainty learning framework for dense neural simultaneous localization and mapping (SLAM). Estimating pixel-wise uncertainties for the depth input of dense SLAM methods allows re-weighing the tracking and mapping losses towards image regions that contain more suitable information that is more reliable for SLAM. To this end, we propose an online framework for sensor uncertainty estimation that can be trained in a self-supervised manner from only 2D input data. We further discuss the advantages … Show more
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