Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Multi-Branch Aggregation Network for Real-Time Semantic
  Segmentation in Street Scenes   Real-time semantic segmentation, which aims to achieve high segmentation
accuracy at real-time inference speed, has received substantial attention over
the past few years. However, many state-of-the-art real-time semantic
segmentation methods tend to sacrifice some spatial details or contextual
information for fast inference, thus leading to degradation in segmentation
quality. In this paper, we propose a novel Deep Multi-branch Aggregation
Network (called DMA-Net) based on the encoder-decoder structure to perform
real-time semantic segmentation in street scenes. Specifically, we first adopt
ResNet-18 as the encoder to efficiently generate various levels of feature maps
from different stages of convolutions. Then, we develop a Multi-branch
Aggregation Network (MAN) as the decoder to effectively aggregate different
levels of feature maps and capture the multi-scale information. In MAN, a
lattice enhanced residual block is designed to enhance feature representations
of the network by taking advantage of the lattice structure. Meanwhile, a
feature transformation block is introduced to explicitly transform the feature
map from the neighboring branch before feature aggregation. Moreover, a global
context block is used to exploit the global contextual information. These key
components are tightly combined and jointly optimized in a unified network.
Extensive experimental results on the challenging Cityscapes and CamVid
datasets demonstrate that our proposed DMA-Net respectively obtains 77.0% and
73.6% mean Intersection over Union (mIoU) at the inference speed of 46.7 FPS
and 119.8 FPS by only using a single NVIDIA GTX 1080Ti GPU. This shows that
DMA-Net provides a good tradeoff between segmentation quality and speed for
semantic segmentation in street scenes.

8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
3
The categories of this paper are: physics
18
The categories of this paper are: econ
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin