Deep fake Face Masks for the Age of Infectious Diseases, Based on An Exception Model.

Abstract

Given the recent infectious disease outbreak, efficient and adaptive protective actions must be in place to slow transmission while keeping social interaction going. The project offers a creative solution by incorporating deepfake technology into face mask design and leveraging an exception model to boost functionality and user experience. With the use of sophisticated deep teaching methods, our system generates masks dynamic, natural-looking facial masks that adapt to individual facial features and expressions, enhancing comfort and compliance. The exception models allow the system to recognize and adapt to one-of-a-kind facial variations and environment conditions to achieve maximum masks fit and filtration efficiency. This integration of deepfake methods and personal protective gear is a new paradigm in public health apparatus, with a possible outbreak of an infectious disease, facial masks' acceptance and efficacy rise. Experimental outcomes visually demonstrate the capability of the model to create masks that initially conform to users' actions, indicating its useful decoration. This research paves the way for subsequent research in intelligent, personal protective equipment that integrates safety and social connectivity.