Deepfakes: evolution and trends

Abstract

This study conducts research on deepfakes technology evolution and trends based on a bibliometric analysis of the articles published on this topic along with six research questions: What are the main research areas of the articles in deepfakes? What are the main current topics in deepfakes research and how are they related? Which are the trends in deepfakes research? How do topics in deepfakes research change over time? Who is researching deepfakes? Who is funding deepfakes research? We have found a total of 331 research articles about deepfakes in an analysis carried out on the Web of Science and Scopus databases. This data serves to provide a complete overview of deepfakes. Main insights include: different areas in which deepfakes research is being performed; which areas are the emerging ones, those that are considered basic, and those that currently have the most potential for development; most studied topics on deepfakes research, including the different artificial intelligence methods applied; emerging and niche topics; relationships among the most prominent researchers; the countries where deepfakes research is performed; main funding institutions. This paper identifies the current trends and opportunities in deepfakes research for practitioners and researchers who want to get into this topic.

A Visual Computing Unified Application Using Deep Learning and Computer Vision Techniques

“…Deepfakes are a prominent application of AI generation within the field of visual computing. They refer to the synthesis of highly convincing, yet entirely fabricated, visual content, with a specific focus on face swapping and face re-enactment [5]. Deepfakes have attracted significant attention due to their potential for both creative applications and misuse, raising concerns about their ethical and legal implications.…”