Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Survey on the attention based RNN model and its applications in computer
  vision   The recurrent neural networks (RNN) can be used to solve the sequence to
sequence problem, where both the input and the output have sequential
structures. Usually there are some implicit relations between the structures.
However, it is hard for the common RNN model to fully explore the relations
between the sequences. In this survey, we introduce some attention based RNN
models which can focus on different parts of the input for each output item, in
order to explore and take advantage of the implicit relations between the input
and the output items. The different attention mechanisms are described in
detail. We then introduce some applications in computer vision which apply the
attention based RNN models. The superiority of the attention based RNN model is
shown by the experimental results. At last some future research directions are
given.

4
The categories of this paper are: cond-mat
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
16
The categories of this paper are: stat