Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: 3D Hand Pose Estimation using Simulation and Partial-Supervision with a
  Shared Latent Space   Tremendous amounts of expensive annotated data are a vital ingredient for
state-of-the-art 3d hand pose estimation. Therefore, synthetic data has been
popularized as annotations are automatically available. However, models trained
only with synthetic samples do not generalize to real data, mainly due to the
gap between the distribution of synthetic and real data. In this paper, we
propose a novel method that seeks to predict the 3d position of the hand using
both synthetic and partially-labeled real data. Accordingly, we form a shared
latent space between three modalities: synthetic depth image, real depth image,
and pose. We demonstrate that by carefully learning the shared latent space, we
can find a regression model that is able to generalize to real data. As such,
we show that our method produces accurate predictions in both semi-supervised
and unsupervised settings. Additionally, the proposed model is capable of
generating novel, meaningful, and consistent samples from all of the three
domains. We evaluate our method qualitatively and quantitively on two highly
competitive benchmarks (i.e., NYU and ICVL) and demonstrate its superiority
over the state-of-the-art methods. The source code will be made available at
https://github.com/masabdi/LSPS.

13
The categories of this paper are: quant-ph
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The categories of this paper are: chao-dyn
35
The categories of this paper are: mtrl-th
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The categories of this paper are: nlin
37
The categories of this paper are: supr-con
11
The categories of this paper are: hep-lat
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
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The categories of this paper are: plasm-ph
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The categories of this paper are: eess
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The categories of this paper are: hep-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: bayes-an