Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Guidance and Teaching Network for Video Salient Object Detection   Owing to the difficulties of mining spatial-temporal cues, the existing
approaches for video salient object detection (VSOD) are limited in
understanding complex and noisy scenarios, and often fail in inferring
prominent objects. To alleviate such shortcomings, we propose a simple yet
efficient architecture, termed Guidance and Teaching Network (GTNet), to
independently distil effective spatial and temporal cues with implicit guidance
and explicit teaching at feature- and decision-level, respectively. To be
specific, we (a) introduce a temporal modulator to implicitly bridge features
from motion into the appearance branch, which is capable of fusing cross-modal
features collaboratively, and (b) utilise motion-guided mask to propagate the
explicit cues during the feature aggregation. This novel learning strategy
achieves satisfactory results via decoupling the complex spatial-temporal cues
and mapping informative cues across different modalities. Extensive experiments
on three challenging benchmarks show that the proposed method can run at ~28
fps on a single TITAN Xp GPU and perform competitively against 14 cutting-edge
baselines.

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The categories of this paper are: hep-ph
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
8
The categories of this paper are: hep-ex
14
The categories of this paper are: math-ph
7
The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
2
The categories of this paper are: math
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
10
The categories of this paper are: q-bio
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con