Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Frontal Low-rank Random Tensors for Fine-grained Action Segmentation   Fine-grained action segmentation in long untrimmed videos is an important
task for many applications such as surveillance, robotics, and human-computer
interaction. To understand subtle and precise actions within a long time
period, second-order information (e.g. feature covariance) or higher is
reported to be effective in the literature. However, extracting such high-order
information is considerably non-trivial. In particular, the dimensionality
increases exponentially with the information order, and hence gaining more
representation power also increases the computational cost and the risk of
overfitting. In this paper, we propose an approach to representing high-order
information for temporal action segmentation via a simple yet effective
bilinear form. Specifically, our contributions are: (1) From the multilinear
perspective, we derive a bilinear form of low complexity, assuming that the
three-way tensor has low-rank frontal slices. (2) Rather than learning the
tensor entries from data, we sample the entries from different underlying
distributions, and prove that the underlying distribution influences the
information order. (3) We employed our bilinear form as an intermediate layer
in state-of-the-art deep neural networks, enabling to represent high-order
information in complex deep models effectively and efficiently. Our
experimental results demonstrate that the proposed bilinear form outperforms
the previous state-of-the-art methods on the challenging temporal action
segmentation task. One can see our project page for data, model and code:
\url{https://vlg.inf.ethz.ch/projects/BilinearTCN/}.

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The categories of this paper are: acc-phys
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The categories of this paper are: atom-ph
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The categories of this paper are: adap-org
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
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The categories of this paper are: solv-int
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The categories of this paper are: supr-con
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-ex
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The categories of this paper are: cmp-lg
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The categories of this paper are: ao-sci
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The categories of this paper are: physics
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The categories of this paper are: hep-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: q-bio