Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Learning-Based Human Pose Estimation: A Survey   Human pose estimation aims to locate the human body parts and build human
body representation (e.g., body skeleton) from input data such as images and
videos. It has drawn increasing attention during the past decade and has been
utilized in a wide range of applications including human-computer interaction,
motion analysis, augmented reality, and virtual reality. Although the recently
developed deep learning-based solutions have achieved high performance in human
pose estimation, there still remain challenges due to insufficient training
data, depth ambiguities, and occlusion. The goal of this survey paper is to
provide a comprehensive review of recent deep learning-based solutions for both
2D and 3D pose estimation via a systematic analysis and comparison of these
solutions based on their input data and inference procedures. More than 250
research papers since 2014 are covered in this survey. Furthermore, 2D and 3D
human pose estimation datasets and evaluation metrics are included.
Quantitative performance comparisons of the reviewed methods on popular
datasets are summarized and discussed. Finally, the challenges involved,
applications, and future research directions are concluded. A regularly updated
project page is provided: \url{https://github.com/zczcwh/DL-HPE}

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The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph