Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Night-time Scene Parsing with a Large Real Dataset   Although huge progress has been made on scene analysis in recent years, most
existing works assume the input images to be in day-time with good lighting
conditions. In this work, we aim to address the night-time scene parsing (NTSP)
problem, which has two main challenges: 1) labeled night-time data are scarce,
and 2) over- and under-exposures may co-occur in the input night-time images
and are not explicitly modeled in existing pipelines. To tackle the scarcity of
night-time data, we collect a novel labeled dataset, named {\it NightCity}, of
4,297 real night-time images with ground truth pixel-level semantic
annotations. To our knowledge, NightCity is the largest dataset for NTSP. In
addition, we also propose an exposure-aware framework to address the NTSP
problem through augmenting the segmentation process with explicitly learned
exposure features. Extensive experiments show that training on NightCity can
significantly improve NTSP performances and that our exposure-aware model
outperforms the state-of-the-art methods, yielding top performances on our
dataset as well as existing datasets.

30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin