Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On Detecting GANs and Retouching based Synthetic Alterations   Digitally retouching images has become a popular trend, with people posting
altered images on social media and even magazines posting flawless facial
images of celebrities. Further, with advancements in Generative Adversarial
Networks (GANs), now changing attributes and retouching have become very easy.
Such synthetic alterations have adverse effect on face recognition algorithms.
While researchers have proposed to detect image tampering, detecting GANs
generated images has still not been explored. This paper proposes a supervised
deep learning algorithm using Convolutional Neural Networks (CNNs) to detect
synthetically altered images. The algorithm yields an accuracy of 99.65% on
detecting retouching on the ND-IIITD dataset. It outperforms the previous state
of the art which reported an accuracy of 87% on the database. For
distinguishing between real images and images generated using GANs, the
proposed algorithm yields an accuracy of 99.83%.

20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
9
The categories of this paper are: nlin
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas