Deep Forgery Detection

Deep forgery detection focuses on identifying manipulated images and videos created using advanced deep learning techniques, aiming to mitigate the spread of misinformation and fraudulent content. Current research emphasizes developing robust detection methods that are resilient to various forgery techniques, including those involving compression artifacts and GAN-generated images, often employing techniques like frequency analysis, multi-view learning, and self-supervised pre-training to enhance model performance. These advancements are crucial for safeguarding digital security and combating the increasing prevalence of sophisticated deepfakes across various applications, from document verification to biometric authentication.