AI RESEARCH
Detecting AI-Generated Images via Contextual Anomaly Estimation in Masked AutoEncoders
arXiv CS.CV
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ArXi:2511.06325v2 Announce Type: replace Context-based detection methods such as DetectGPT achieve strong generalization in identifying AI-generated text by evaluating content compatibility with a model's learned distribution. In contrast, existing image detectors rely on discriminative features from pretrained backbones such as CLIP, which implicitly capture generator-specific artifacts. However, as modern generative models rapidly advance in visual fidelity, the artifacts these detectors depend on are becoming increasingly subtle or absent, undermining their reliability.