STUN: Self-Teaching Uncertainty Estimation for Place Recognition. (arXiv:2203.01851v2 [cs.CV] UPDATED)

Place recognition is key to Simultaneous Localization and Mapping (SLAM) and
spatial perception. However, a place recognition in the wild often suffers from
erroneous predictions due to image variations, e.g., changing viewpoints and
street appearance. Integrating uncertainty estimation into the life cycle of
place recognition is a promising method to mitigate the impact of variations on
place recognition performance. However, existing uncertainty estimation
approaches in this vein are either computationally inefficient (e.g., Monte
Carlo dropout) or at the cost of …

arxiv teaching uncertainty