Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unmasking DeepFakes with simple Features   Deep generative models have recently achieved impressive results for many
real-world applications, successfully generating high-resolution and diverse
samples from complex datasets. Due to this improvement, fake digital contents
have proliferated growing concern and spreading distrust in image content,
leading to an urgent need for automated ways to detect these AI-generated fake
images.
  Despite the fact that many face editing algorithms seem to produce realistic
human faces, upon closer examination, they do exhibit artifacts in certain
domains which are often hidden to the naked eye. In this work, we present a
simple way to detect such fake face images - so-called DeepFakes. Our method is
based on a classical frequency domain analysis followed by basic classifier.
Compared to previous systems, which need to be fed with large amounts of
labeled data, our approach showed very good results using only a few annotated
training samples and even achieved good accuracies in fully unsupervised
scenarios. For the evaluation on high resolution face images, we combined
several public datasets of real and fake faces into a new benchmark: Faces-HQ.
Given such high-resolution images, our approach reaches a perfect
classification accuracy of 100% when it is trained on as little as 20 annotated
samples. In a second experiment, in the evaluation of the medium-resolution
images of the CelebA dataset, our method achieves 100% accuracy supervised and
96% in an unsupervised setting. Finally, evaluating a low-resolution video
sequences of the FaceForensics++ dataset, our method achieves 91% accuracy
detecting manipulated videos.
  Source Code: https://github.com/cc-hpc-itwm/DeepFakeDetection

7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
2
The categories of this paper are: math
4
The categories of this paper are: cond-mat
3
The categories of this paper are: physics
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
19
The categories of this paper are: eess
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
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The categories of this paper are: q-fin
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The categories of this paper are: hep-ph