Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fast Template Matching and Update for Video Object Tracking and
  Segmentation   In this paper, the main task we aim to tackle is the multi-instance
semi-supervised video object segmentation across a sequence of frames where
only the first-frame box-level ground-truth is provided. Detection-based
algorithms are widely adopted to handle this task, and the challenges lie in
the selection of the matching method to predict the result as well as to decide
whether to update the target template using the newly predicted result. The
existing methods, however, make these selections in a rough and inflexible way,
compromising their performance. To overcome this limitation, we propose a novel
approach which utilizes reinforcement learning to make these two decisions at
the same time. Specifically, the reinforcement learning agent learns to decide
whether to update the target template according to the quality of the predicted
result. The choice of the matching method will be determined at the same time,
based on the action history of the reinforcement learning agent. Experiments
show that our method is almost 10 times faster than the previous
state-of-the-art method with even higher accuracy (region similarity of 69.1%
on DAVIS 2017 dataset).

2
The categories of this paper are: math
11
The categories of this paper are: hep-lat
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
13
The categories of this paper are: quant-ph
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex