Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Semantically Selective Augmentation for Deep Compact Person
  Re-Identification   We present a deep person re-identification approach that combines
semantically selective, deep data augmentation with clustering-based network
compression to generate high performance, light and fast inference networks. In
particular, we propose to augment limited training data via sampling from a
deep convolutional generative adversarial network (DCGAN), whose discriminator
is constrained by a semantic classifier to explicitly control the domain
specificity of the generation process. Thereby, we encode information in the
classifier network which can be utilized to steer adversarial synthesis, and
which fuels our CondenseNet ID-network training. We provide a quantitative and
qualitative analysis of the approach and its variants on a number of datasets,
obtaining results that outperform the state-of-the-art on the LIMA dataset for
long-term monitoring in indoor living spaces.

33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
6
The categories of this paper are: astro-ph
12
The categories of this paper are: nucl-th