Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Simple Multi-Resolution Representation Learning for Human Pose
  Estimation   Human pose estimation - the process of recognizing human keypoints in a given
image - is one of the most important tasks in computer vision and has a wide
range of applications including movement diagnostics, surveillance, or
self-driving vehicle. The accuracy of human keypoint prediction is increasingly
improved thanks to the burgeoning development of deep learning. Most existing
methods solved human pose estimation by generating heatmaps in which the ith
heatmap indicates the location confidence of the ith keypoint. In this paper,
we introduce novel network structures referred to as multi-resolution
representation learning for human keypoint prediction. At different resolutions
in the learning process, our networks branch off and use extra layers to learn
heatmap generation. We firstly consider the architectures for generating the
multi-resolution heatmaps after obtaining the lowest-resolution feature maps.
Our second approach allows learning during the process of feature extraction in
which the heatmaps are generated at each resolution of the feature extractor.
The first and second approaches are referred to as multi-resolution heatmap
learning and multi-resolution feature map learning respectively. Our
architectures are simple yet effective, achieving good performance. We
conducted experiments on two common benchmarks for human pose estimation:
MSCOCO and MPII dataset. The code is made publicly available at
https://github.com/tqtrunghnvn/SimMRPose.

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The categories of this paper are: dg-ga
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The categories of this paper are: chem-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: hep-ex
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
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The categories of this paper are: alg-geom
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The categories of this paper are: comp-gas
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The categories of this paper are: hep-th
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The categories of this paper are: atom-ph
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The categories of this paper are: q-alg
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The categories of this paper are: plasm-ph
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The categories of this paper are: cond-mat
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The categories of this paper are: bayes-an
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The categories of this paper are: econ
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The categories of this paper are: chao-dyn