BareFace Restoration: Using ResNet-34 for Makeup Removal

Abstract

We currently investigate the use of ResNet-34 as an encoder in the U-Net architecture, in the field of decoupling. This problem poses a major challenge because cosmetics obscure basic facial features, which is important in applications in many fields of security, entertainment and social networks. By effectively exploiting deep learning techniques to automatically remove makeup from facial images. The algorithm enhances the performance and feature extraction capabilities inherent in ResNet-34. Through testing, the results have shown that this new makeup removal model is very effective. It helps to remove makeup that not only simplifies the process but also contributes significantly to advancing computer vision applications. This investigation represents an important step forward in the development of smart solutions for image enhancement and potential applications. The architectural framework of U-Net with ResNet-34 as the encoder contributes significantly to achieving these advances.