Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: STUN: Self-Teaching Uncertainty Estimation for Place Recognition   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 dropped accuracy. This paper proposes STUN, a
self-teaching framework that learns to simultaneously predict the place and
estimate the prediction uncertainty given an input image. To this end, we first
train a teacher net using a standard metric learning pipeline to produce
embedding priors. Then, supervised by the pretrained teacher net, a student net
with an additional variance branch is trained to finetune the embedding priors
and estimate the uncertainty sample by sample. During the online inference
phase, we only use the student net to generate a place prediction in
conjunction with the uncertainty. When compared with place recognition systems
that are ignorant to the uncertainty, our framework features the uncertainty
estimation for free without sacrificing any prediction accuracy. Our
experimental results on the large-scale Pittsburgh30k dataset demonstrate that
STUN outperforms the state-of-the-art methods in both recognition accuracy and
the quality of uncertainty estimation.

16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th