DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection

Rui Shao^1,2 Tianxing Wu² Liqiang Nie¹ Ziwei Liu²

¹School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen)
²S-Lab, Nanyang Technological University

[Paper]

:fire: Code will be released. Stay tuned :beers: :+1:

We propose a novel DeepFake-Adapter, which is a dual-level adapter composed of Globally-aware Bottleneck Adapters (GBA) and Locally-aware Spatial Adapters (LSA). DeepFake-Adapter can effectively adapt a pre-trained ViT by enabling high-level semantics from ViT to organically interact with global and local low-level forgeries from adapters. This contributes to more generalizable forgery representations for deepfake detection.