DECODE: Tackling Representation and Decision Degradation in Continual AI-Generated Image Detection
DECODE is proposed, a decoupled continual detection framework that jointly mitigates representation- and decision-level forgetting and introduces Subspace Diversity Regularization to preserve diverse forensic representations and Closed-Form Decision Alignment to recalibrate the shared classification head after each ada...