Publication

Abstract : In todays world, where concerns about privacy are on the rise the use of techniques to mask faces and protect individuals identities in multimedia content has become extremely important. This study thoroughly examines methods of anonymization with a specific focus on how Generative Adversarial Networks (GANs) can be used to enhance privacy preservation. By conducting an analysis that includes techniques like Gaussian Blur, Pixelation, Deep Learning and hybrid approaches our research highlights the impressive effectiveness of GAN based anonymization. This innovative approach not effectively hides identities but also ensures that the anonymized content remains understandable and usable. Alongside evaluating existing techniques our paper also sets the stage for exploration, in this field with the goal of advancing face masking anonymization techniques.