A Qualitative Survey on Deep Learning Based Deep fake Video Creation and Detection Method
Published: 2 February 2022
Australian Journal of Engineering and Innovative Technology pp 13-26; https://doi.org/10.34104/ajeit.022.013026
Abstract: The rapid growth of Deep Learning (DL) based applications is taking place in this modern world. Deep Learning is used to solve so many critical problems such as big data analysis, computer vision, and human brain interfacing. The advancement of deep learning can also causes some national and some international threats to privacy, democracy, and national security. Deepfake videos are growing so fast having an impact on political, social, and personal life. Deepfake videos use artificial intelligence and can appear very convincing, even to a trained eye. Often obscene videos are made using deepfakes which tarnishes people's reputation. Deepfakes are a general public concern, thus it's important to develop methods to detect them. This survey paper includes a survey of deepfake creation algorithms and, more crucially we added some approaches of deepfake detection that proposed by researchers to date. Here we go over the problems, trends in the field, and future directions for deepfake technology in detail. This paper gives a complete overview of deepfake approaches and supports the implementation of novel and more reliable methods to cope with the highly complicated deepfakes by studying the background of deepfakes and state-of-the-art deepfake detection methods.
Keywords: survey / Deep Learning / Creation / Deepfake videos / deepfake approaches / deepfake detection
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