Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Lifting from the Deep: Convolutional 3D Pose Estimation from a Single
  Image   We propose a unified formulation for the problem of 3D human pose estimation
from a single raw RGB image that reasons jointly about 2D joint estimation and
3D pose reconstruction to improve both tasks. We take an integrated approach
that fuses probabilistic knowledge of 3D human pose with a multi-stage CNN
architecture and uses the knowledge of plausible 3D landmark locations to
refine the search for better 2D locations. The entire process is trained
end-to-end, is extremely efficient and obtains state- of-the-art results on
Human3.6M outperforming previous approaches both on 2D and 3D errors.

36
The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
12
The categories of this paper are: nucl-th
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The categories of this paper are: q-alg
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The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th