Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Anchor-free 3D Single Stage Detector with Mask-Guided Attention for
  Point Cloud   Most of the existing single-stage and two-stage 3D object detectors are
anchor-based methods, while the efficient but challenging anchor-free
single-stage 3D object detection is not well investigated. Recent studies on 2D
object detection show that the anchor-free methods also are of great potential.
However, the unordered and sparse properties of point clouds prevent us from
directly leveraging the advanced 2D methods on 3D point clouds. We overcome
this by converting the voxel-based sparse 3D feature volumes into the sparse 2D
feature maps. We propose an attentive module to fit the sparse feature maps to
dense mostly on the object regions through the deformable convolution tower and
the supervised mask-guided attention. By directly regressing the 3D bounding
box from the enhanced and dense feature maps, we construct a novel single-stage
3D detector for point clouds in an anchor-free manner. We propose an IoU-based
detection confidence re-calibration scheme to improve the correlation between
the detection confidence score and the accuracy of the bounding box regression.
Our code is publicly available at \url{https://github.com/jialeli1/MGAF-3DSSD}.

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The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
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The categories of this paper are: solv-int
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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: chem-ph
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The categories of this paper are: eess
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
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The categories of this paper are: adap-org
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The categories of this paper are: alg-geom
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-ex
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The categories of this paper are: nucl-th
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The categories of this paper are: patt-sol