This project uses Matterport’s Mask R-CNN deep learning model to detect and segment censor bars and mosaic regions in images. It employs ESRGAN (a GAN-based super-resolution model) to decensor mosaic areas and reconstruct the underlying content. The system is designed to automate the detection pipeline that previously required manual annotation of censor locations.