Band-Attention Modulated RetNet for Face Forgery Detection

arXiv:2404.06022v1 Announce Type: new
Abstract: The transformer networks are extensively utilized in face forgery detection due to their scalability across large datasets.Despite their success, transformers face challenges in balancing the capture of global context, which is crucial for unveiling forgery clues, with computational complexity.To mitigate this issue, we introduce Band-Attention modulated RetNet (BAR-Net), a lightweight network designed to efficiently process extensive visual contexts while avoiding catastrophic forgetting.Our approach empowers the target token to perceive global information by assigning differential attention …

abstract arxiv attention challenges complexity computational context cs.ai cs.cv cs.mm datasets detection face forgery global issue large datasets networks scalability success transformer transformers type