Advances in image generation have made synthetic images increasingly difficult to distinguish from real photographs, raising concerns about the trustworthiness of visual media. Existing AI-generated image detectors often perform well on in-domain data, but their robustness and cross-generator generalization remain limi...
Man-Ni Cui, Rui-Qi Liu, Zi-Jian Yu et al.· 0 citations
This work constructs a benchmark that captures unintended degradation on benign inputs sharing generic patterns with the forget set, and proposes Selective Protection with Anchored Regularization, which protects generic patterns via anchored activation filtering while reinforcing them through entity-abstracted enhancem...
Junxian You, Junkai Chen, Yuhao He et al.· 0 citations
The proposed GlobalForge improves average BAcc on 8 in-the-wild benchmark groups by $\mathbf{5.89\%}$ over the previous state-of-the-art, and is clearly ahead of representative baselines on RealDeg-Bench under both single and compound degradations.
Manni Cui, Ruiqi Liu, Dianyuan Zou et al.· arXiv.org· 0 citations
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