Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robust Visual Odometry Using Position-Aware Flow and Geometric Bundle
  Adjustment   In this paper, an essential problem of robust visual odometry (VO) is
approached by incorporating geometry-based methods into deep-learning
architecture in a self-supervised manner. Generally, pure geometry-based
algorithms are not as robust as deep learning in feature-point extraction and
matching, but perform well in ego-motion estimation because of their
well-established geometric theory. In this work, a novel optical flow network
(PANet) built on a position-aware mechanism is proposed first. Then, a novel
system that jointly estimates depth, optical flow, and ego-motion without a
typical network to learning ego-motion is proposed. The key component of the
proposed system is an improved bundle adjustment module containing multiple
sampling, initialization of ego-motion, dynamic damping factor adjustment, and
Jacobi matrix weighting. In addition, a novel relative photometric loss
function is advanced to improve the depth estimation accuracy. The experiments
show that the proposed system not only outperforms other state-of-the-art
methods in terms of depth, flow, and VO estimation among self-supervised
learning-based methods on KITTI dataset, but also significantly improves
robustness compared with geometry-based, learning-based and hybrid VO systems.
Further experiments show that our model achieves outstanding generalization
ability and performance in challenging indoor (TMU-RGBD) and outdoor (KAIST)
scenes.

25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int