Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Unified Structure for Efficient RGB and RGB-D Salient Object Detection   Salient object detection (SOD) has been well studied in recent years,
especially using deep neural networks. However, SOD with RGB and RGB-D images
is usually treated as two different tasks with different network structures
that need to be designed specifically. In this paper, we proposed a unified and
efficient structure with a cross-attention context extraction (CRACE) module to
address both tasks of SOD efficiently. The proposed CRACE module receives and
appropriately fuses two (for RGB SOD) or three (for RGB-D SOD) inputs. The
simple unified feature pyramid network (FPN)-like structure with CRACE modules
conveys and refines the results under the multi-level supervisions of saliency
and boundaries. The proposed structure is simple yet effective; the rich
context information of RGB and depth can be appropriately extracted and fused
by the proposed structure efficiently. Experimental results show that our
method outperforms other state-of-the-art methods in both RGB and RGB-D SOD
tasks on various datasets and in terms of most metrics.

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The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
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The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
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The categories of this paper are: econ
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The categories of this paper are: alg-geom
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The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc