A Survey of Deepfake Detection Methods

被引：0
|
作者：
Yildiz, Burak Ikan [1 ]
Gokberk, Berk [1 ]
机构：
[1] Bogazici Univ, Bilgisayar Muhendisligi, Istanbul, Turkiye
来源：
2023 31ST SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, SIU | 2023年
关键词：
deepfake; deep learning; computer vision;
D O I：
10.1109/SIU59756.2023.10223820
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this work, we examine recent methods employed for detecting deepfake images and videos, which have become increasingly prevalent in recent times. Deepfake datasets are categorized into generations based on the number of data, quality, and diversity of the data they contain, and a new realistic dataset has been generated to accurately reflect real-world conditions. In this paper, we evaluate the methodologies used for deepfake detection using computer vision and deep learning on currently available datasets and present the results in a comprehensive manner.
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页数：4
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