Forensic Reserve: Eliciting Latent Knowledge for Image Forgery Detection
As generated images become increasingly realistic, reliable forgery detection is essential for maintaining trust in visual information. However, existing methods primarily rely on task-specific supervision to adapt vision foundation model representations, without fully exploiting internal forensic knowledge to guide detection. To address this limitation, we propose Reserve-Guided Elicitation (RGE), a framework that treats sparse, origin-sensitive internal components in pretrained models as a forensic reserve and translates their localization into structural constraints for lightweight adaptation. Specifically, we first use the Forensic Lens (F-lens) to decompose activations across layers ...
| Authors | Jiahua Li, Zixu John, Tom Zhong et al. |
|---|---|
| Primary category | cs.CV |
| Published | 6 October 2026 |
| Last updated at source | 6 October 2026 |
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