Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DeepAVO: Efficient Pose Refining with Feature Distilling for Deep Visual
  Odometry   The technology for Visual Odometry (VO) that estimates the position and
orientation of the moving object through analyzing the image sequences captured
by on-board cameras, has been well investigated with the rising interest in
autonomous driving. This paper studies monocular VO from the perspective of
Deep Learning (DL). Unlike most current learning-based methods, our approach,
called DeepAVO, is established on the intuition that features contribute
discriminately to different motion patterns. Specifically, we present a novel
four-branch network to learn the rotation and translation by leveraging
Convolutional Neural Networks (CNNs) to focus on different quadrants of optical
flow input. To enhance the ability of feature selection, we further introduce
an effective channel-spatial attention mechanism to force each branch to
explicitly distill related information for specific Frame to Frame (F2F) motion
estimation. Experiments on various datasets involving outdoor driving and
indoor walking scenarios show that the proposed DeepAVO outperforms the
state-of-the-art monocular methods by a large margin, demonstrating competitive
performance to the stereo VO algorithm and verifying promising potential for
generalization.

17
The categories of this paper are: q-fin
19
The categories of this paper are: eess
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
16
The categories of this paper are: stat
11
The categories of this paper are: hep-lat
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga