Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: FSGAN: Subject Agnostic Face Swapping and Reenactment   We present Face Swapping GAN (FSGAN) for face swapping and reenactment.
Unlike previous work, FSGAN is subject agnostic and can be applied to pairs of
faces without requiring training on those faces. To this end, we describe a
number of technical contributions. We derive a novel recurrent neural network
(RNN)-based approach for face reenactment which adjusts for both pose and
expression variations and can be applied to a single image or a video sequence.
For video sequences, we introduce continuous interpolation of the face views
based on reenactment, Delaunay Triangulation, and barycentric coordinates.
Occluded face regions are handled by a face completion network. Finally, we use
a face blending network for seamless blending of the two faces while preserving
target skin color and lighting conditions. This network uses a novel Poisson
blending loss which combines Poisson optimization with perceptual loss. We
compare our approach to existing state-of-the-art systems and show our results
to be both qualitatively and quantitatively superior.

2
The categories of this paper are: math
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
14
The categories of this paper are: math-ph
34
The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
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The categories of this paper are: physics
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci