Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Tracking: Visual Tracking Using Deep Convolutional Networks   In this paper, we study a discriminatively trained deep convolutional network
for the task of visual tracking. Our tracker utilizes both motion and
appearance features that are extracted from a pre-trained dual stream deep
convolution network. We show that the features extracted from our dual-stream
network can provide rich information about the target and this leads to
competitive performance against state of the art tracking methods on a visual
tracking benchmark.

26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int