Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in
  Video Classification   Despite the steady progress in video analysis led by the adoption of
convolutional neural networks (CNNs), the relative improvement has been less
drastic as that in 2D static image classification. Three main challenges exist
including spatial (image) feature representation, temporal information
representation, and model/computation complexity. It was recently shown by
Carreira and Zisserman that 3D CNNs, inflated from 2D networks and pretrained
on ImageNet, could be a promising way for spatial and temporal representation
learning. However, as for model/computation complexity, 3D CNNs are much more
expensive than 2D CNNs and prone to overfit. We seek a balance between speed
and accuracy by building an effective and efficient video classification system
through systematic exploration of critical network design choices. In
particular, we show that it is possible to replace many of the 3D convolutions
by low-cost 2D convolutions. Rather surprisingly, best result (in both speed
and accuracy) is achieved when replacing the 3D convolutions at the bottom of
the network, suggesting that temporal representation learning on high-level
semantic features is more useful. Our conclusion generalizes to datasets with
very different properties. When combined with several other cost-effective
designs including separable spatial/temporal convolution and feature gating,
our system results in an effective video classification system that that
produces very competitive results on several action classification benchmarks
(Kinetics, Something-something, UCF101 and HMDB), as well as two action
detection (localization) benchmarks (JHMDB and UCF101-24).

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The categories of this paper are: nlin
19
The categories of this paper are: eess
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
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The categories of this paper are: nucl-ex
30
The categories of this paper are: q-alg
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-th
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The categories of this paper are: comp-gas
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The categories of this paper are: q-bio
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The categories of this paper are: supr-con
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The categories of this paper are: cmp-lg
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The categories of this paper are: adap-org
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The categories of this paper are: cond-mat
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The categories of this paper are: funct-an