Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Two-Stream Consensus Network for Weakly-Supervised Temporal Action
  Localization   Weakly-supervised Temporal Action Localization (W-TAL) aims to classify and
localize all action instances in an untrimmed video under only video-level
supervision. However, without frame-level annotations, it is challenging for
W-TAL methods to identify false positive action proposals and generate action
proposals with precise temporal boundaries. In this paper, we present a
Two-Stream Consensus Network (TSCN) to simultaneously address these challenges.
The proposed TSCN features an iterative refinement training method, where a
frame-level pseudo ground truth is iteratively updated, and used to provide
frame-level supervision for improved model training and false positive action
proposal elimination. Furthermore, we propose a new attention normalization
loss to encourage the predicted attention to act like a binary selection, and
promote the precise localization of action instance boundaries. Experiments
conducted on the THUMOS14 and ActivityNet datasets show that the proposed TSCN
outperforms current state-of-the-art methods, and even achieves comparable
results with some recent fully-supervised methods.

9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th
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The categories of this paper are: nucl-ex
2
The categories of this paper are: math
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
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The categories of this paper are: econ
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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: q-alg