Detecting Deepfake Videos Using Euler Video Magnification

Recent advances in artificial intelligence make it progressively hard to distinguish between genuine and counterfeit media, especially images videos. One recent development is the rise of deepfake videos, based on manipulating videos using advanced machine learning techniques. This involves replacing face an individual from a source video with second person, destination video. idea becoming refined as deepfakes are getting seamless simpler compute. Combined outreach speed social could easily fool individuals when depicting someone saying things that never happened thus persuade people believing fictional scenarios, creating distress, spreading fake news. In this paper, we examine technique for possible identification We use Euler magnification which applies spatial decomposition temporal filtering data highlight magnify hidden features like skin pulsation subtle motions. Our approach uses extracted train three models classify unaltered compare results existing