SECURAFACE - DEEP LEARNING MODEL TO CREATE SYNTHETIC IMAGES AND VIDEOS

Abstract

The "SecuraFace" project investigates the development of synthetic films using deep learning and deepfake ideas. This project intends to create a system that can generate very realistic video sequences, allowing exact control and manipulation of the activities of a target, similar to a puppeteer directing a marionette. The project aims to push the frontiers of visual manipulation by combining advanced deep learning models and computer vision algorithms, providing a powerful tool for entertainment, virtual production, and video editing applications. The "SecuraFace" technology, which combines face identification, facial landmark tracking, and face synthesis algorithms, allows users to seamlessly incorporate synthetic faces into movies, giving them intuitive control over the target person's expressions and movements. This innovative approach also enables the creation of lifelike avatars for virtual reality environments, enhancing user interaction and immersion. Additionally, the system can be utilized for dubbing and localization of foreign films, providing precise lip synchronization and expression matching to maintain the authenticity of the performance across different languages. The project's findings demonstrate the system's promise while emphasizing the significance of responsible use and ethical issues in the field of deepfake technology. The development of guidelines and safeguards is crucial to ensure that such powerful tools are not misused, and the project underscores the importance of a balanced approach between technological Advancement and ethical responsibility.