# A Comprehensive Survey of Masked Faces: Recognition, Detection, and Unmasking
## 1 Introduction
### Applications of MFR  
MFR exhibits significant potential in numerous sectors, providing a secure and efficient means of identity verification in scenarios where individuals are wearing face masks. This potential translates into innovative solutions addressing contemporary challenges. This subsection explores the diverse applications where MFR can be leveraged, showcasing its adaptability and relevance. * Security and Access Control: Strengthening security measures to achieve precise identification, especially in scenarios involving individuals wearing masks. Seamlesslyintegrating with access control systems to guarantee secure entry across public and private spaces, including restricted areas like airports, government buildings, and data centers. Additionally, implementing facial recognition-based door locks for both residential and office settings, enhancing home and workplace security. Enabling employee authentication protocols for secure entry into workplaces. * Public Safety: MFR plays a crucial role in safeguarding public safety in crowded spaces. Integrated seamlessly with surveillance systems, MFR empowers law enforcement with enhanced monitoring and rapid response capabilities. This technology aids in identifying suspects and missing persons involved in criminal investigations, proactively detects suspicious activity in public areas, swiftly pinpoints individuals involved in disturbances, and strengthens security measures at events and gatherings. MFR's potential to enhance public safety and create a secure environment is undeniable. * Healthcare: Ensuring secure access to medical facilities and patient records, along with verifying the identity of both patients and healthcare workers. Implementing contactless patient tracking to elevate healthcare services while simultaneously fortifying security and privacy within healthcare settings. * Retail and Customer Service: Delivering tailored and efficient customer service by recognizing individuals, even when their faces are partially obscured. Additionally, optimizing payment processes to elevate the overall shopping experience. * Human-Computer Interaction: Facilitating secure and personalized interactions with user-authenticated devices while also improving the user experience across a spectrum of applications, including smartphones, computers, and smart home devices. * Workplace and Attendance Tracking: Facilitating contactless attendance tracking for employees in workplace settings, thereby reinforcing security measures to grant access exclusively to authorized individuals in designated areas. * Education Institutions: Overseing and securing entry points in educational institutions to safeguard the well-being of students and staff. Streamlining attendance tracking in classrooms and campus facilities for enhanced efficiency. By exploring these applications and more, it becomes evident that MFR has the potential to revolutionize diverse sectors, providing solutions that cater to the evolving needs of modern society. Contributions of this survey encompass the following:  
1. An in-depth exploration of MFR, FMR, and FU within the framework of deep learning methodologies, highlighting the challenges inherent in identifying individuals with partially obscured facial features. 2. A comprehensive exploration of evaluation metrics, benchmarking methods, and diverse applications of masked face recognition across security, healthcare, and human-computer interaction domains. 3. A detailed analysis of critical datasets and preprocessing methodologies essential for training robust masked face recognition models. 4. Tracing the evolutionary trajectory of face recognition within the deep learning paradigm, providing insights into the development of techniques tailored for identifying and verifying individuals under various degrees of facial occlusion. This investigation into masked face recognition, face mask recognition, and face unmasking, grounded in the advancements of deep learning, aspires to furnish a foundational understanding for researchers.