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Review on Detection of Deepfake in Images and Videos
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 186 - Number 29 |
| Year of Publication: 2024 |
| Authors: Yaramasa Gautham, Sindhu R., Jenitta J. |
10.5120/ijca2024923825
|
Yaramasa Gautham, Sindhu R., Jenitta J. . Review on Detection of Deepfake in Images and Videos. International Journal of Computer Applications. 186, 29 ( Jul 2024), 51-60. DOI=10.5120/ijca2024923825
Abstract
Deepfake technology can manipulate and superimpose existing images or videos onto other images or videos, creating realistic-looking but fabricated content. This technology has raised concerns as it can be used to create deceptive or misleading media, potentially causing harm by spreading false information or manipulating public perception. A detailed review is done on the detection of Deepfake in images and videos and it is presented in this paper. Various methods with which the detection of deepfake can be performed are image-based, video-based, frequency-based, Machine learning algorithm-based and Generative Adversarial-based methods. Various databases used, advantages and drawbacks of each literature are discussed in detail. After thorough research, it was found that the Attentive-pooling methods are giving better results than all the other methods that were proposed in the literature.
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