Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards Fast and Accurate Multi-Person Pose Estimation on Mobile Devices   The rapid development of autonomous driving, abnormal behavior detection, and
behavior recognition makes an increasing demand for multi-person pose
estimation-based applications, especially on mobile platforms. However, to
achieve high accuracy, state-of-the-art methods tend to have a large model size
and complex post-processing algorithm, which costs intense computation and long
end-to-end latency. To solve this problem, we propose an architecture
optimization and weight pruning framework to accelerate inference of
multi-person pose estimation on mobile devices. With our optimization
framework, we achieve up to 2.51x faster model inference speed with higher
accuracy compared to representative lightweight multi-person pose estimator.

19
The categories of this paper are: eess
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph