Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: HAVANA: Hierarchical and Variation-Normalized Autoencoder for Person
  Re-identification   Person Re-Identification (Re-ID) is of great importance to the many video
surveillance systems. Learning discriminative features for Re-ID remains a
challenge due to the large variations in the image space, e.g., continuously
changing human poses, illuminations and point of views. In this paper, we
propose HAVANA, a novel extensible, light-weight HierArchical and
VAriation-Normalized Autoencoder that learns features robust to intra-class
variations. In contrast to existing generative approaches that prune the
variations with heavy extra supervised signals, HAVANA suppresses the
intra-class variations with a Variation-Normalized Autoencoder trained with no
additional supervision. We also introduce a novel Jensen-Shannon triplet loss
for contrastive distribution learning in Re-ID. In addition, we present
Hierarchical Variation Distiller, a hierarchical VAE to factorize the latent
representation and explicitly model the variations. To the best of our
knowledge, HAVANA is the first VAE-based framework for person ReID.

26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
2
The categories of this paper are: math
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics