Fake Document

Fake document research focuses on detecting and generating artificial documents, encompassing images, text, and files, with the primary objective of improving security and understanding the limitations of detection methods. Current research explores various deep learning architectures, including Vision and Language Transformers and Character Texture Perception Networks, to detect forgeries and generate realistic fakes, often focusing on subtle manipulations and the use of synthetic data to augment training sets. This field is crucial for combating fraud and misinformation, impacting areas like cybersecurity, digital forensics, and biometric authentication, while also advancing our understanding of model generalization and the effects of model misspecification.