Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Expression Conditional GAN for Facial Expression-to-Expression
  Translation   In this paper, we focus on the facial expression translation task and propose
a novel Expression Conditional GAN (ECGAN) which can learn the mapping from one
image domain to another one based on an additional expression attribute. The
proposed ECGAN is a generic framework and is applicable to different expression
generation tasks where specific facial expression can be easily controlled by
the conditional attribute label. Besides, we introduce a novel face mask loss
to reduce the influence of background changing. Moreover, we propose an entire
framework for facial expression generation and recognition in the wild, which
consists of two modules, i.e., generation and recognition. Finally, we evaluate
our framework on several public face datasets in which the subjects have
different races, illumination, occlusion, pose, color, content and background
conditions. Even though these datasets are very diverse, both the qualitative
and quantitative results demonstrate that our approach is able to generate
facial expressions accurately and robustly.

7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
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The categories of this paper are: comp-gas
28
The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
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The categories of this paper are: eess