Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Hallucinating Optical Flow Features for Video Classification   Appearance and motion are two key components to depict and characterize the
video content. Currently, the two-stream models have achieved state-of-the-art
performances on video classification. However, extracting motion information,
specifically in the form of optical flow features, is extremely computationally
expensive, especially for large-scale video classification. In this paper, we
propose a motion hallucination network, namely MoNet, to imagine the optical
flow features from the appearance features, with no reliance on the optical
flow computation. Specifically, MoNet models the temporal relationships of the
appearance features and exploits the contextual relationships of the optical
flow features with concurrent connections. Extensive experimental results
demonstrate that the proposed MoNet can effectively and efficiently hallucinate
the optical flow features, which together with the appearance features
consistently improve the video classification performances. Moreover, MoNet can
help cutting down almost a half of computational and data-storage burdens for
the two-stream video classification. Our code is available at:
https://github.com/YongyiTang92/MoNet-Features.

36
The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat