Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Learning for Video Classification and Captioning   Accelerated by the tremendous increase in Internet bandwidth and storage
space, video data has been generated, published and spread explosively,
becoming an indispensable part of today's big data. In this paper, we focus on
reviewing two lines of research aiming to stimulate the comprehension of videos
with deep learning: video classification and video captioning. While video
classification concentrates on automatically labeling video clips based on
their semantic contents like human actions or complex events, video captioning
attempts to generate a complete and natural sentence, enriching the single
label as in video classification, to capture the most informative dynamics in
videos. In addition, we also provide a review of popular benchmarks and
competitions, which are critical for evaluating the technical progress of this
vibrant field.

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The categories of this paper are: bayes-an
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
3
The categories of this paper are: physics