Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular
  Depth Estimation in the Dark   Monocular depth estimation aims at predicting depth from a single image or
video. Recently, self-supervised methods draw much attention since they are
free of depth annotations and achieve impressive performance on several daytime
benchmarks. However, they produce weird outputs in more challenging nighttime
scenarios because of low visibility and varying illuminations, which bring weak
textures and break brightness-consistency assumption, respectively. To address
these problems, in this paper we propose a novel framework with several
improvements: (1) we introduce Priors-Based Regularization to learn
distribution knowledge from unpaired depth maps and prevent model from being
incorrectly trained; (2) we leverage Mapping-Consistent Image Enhancement
module to enhance image visibility and contrast while maintaining brightness
consistency; and (3) we present Statistics-Based Mask strategy to tune the
number of removed pixels within textureless regions, using dynamic statistics.
Experimental results demonstrate the effectiveness of each component.
Meanwhile, our framework achieves remarkable improvements and state-of-the-art
results on two nighttime datasets.

12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
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The categories of this paper are: patt-sol
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
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The categories of this paper are: math-ph
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex