Visual content authenticity detection and deep forged image recognition

With the advancement of multimedia editing technology and image processing technology, using smartphones to complete complex image changes has become possible, posing a threat to personal information security and the authenticity of information dissemination. To address this challenge, Image Manipulation Localization (IML) technology combined with image comparison, spatial domain analysis, and restoration techniques can effectively detect image changes and edits. In recent years, Visual Transformer (VIT) models have become a new choice for capturing images, but Convolutional Neural Networks (CNN) still have shortcomings. To make up for this deficiency, I found the IML-VIT model. This model has the ability of multi-scale feature extraction and high resolution, and supports convergence of a small amount of data. In research and testing, the IML-VIT model has shown high accuracy and completeness, making it the best choice.