November 30, 2025PLoS ONEOpen Access

SCADET: A detection framework for AI-generated artwork integrating dynamic frequency attention and contrastive spectral analysis

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Authors

XZXiaolong Zhang ZYZekai Yu JZJianqiao Zhao

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Implication

The SCADET framework reduces variability in detection of AI-generated images, using Dynamic Frequency Attention and Contrastive Spectral Analysis for enhanced performance.

Key Points

SCADET reduces variability in detecting AI-generated images, achieving notable improvements.
It integrates Dynamic Frequency Attention Network and Contrastive Spectral Analysis Network for enhanced detection.
A comprehensive evaluation on AI-ArtBench dataset shows AUC values of 0.962 and 0.801 for full and local image detection.
The findings advance detection techniques in digital media, addressing authenticity challenges across generation methods.

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Zhang et al. (2025) studied this question.

synapsesocial.com/papers/692b943e1d383f2b2a378a9d https://doi.org/10.1371/journal.pone.0336328

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Implication

The SCADET framework reduces variability in detection of AI-generated images, using Dynamic Frequency Attention and Contrastive Spectral Analysis for enhanced performance.

SCADET: A detection framework for AI-generated artwork integrating dynamic frequency attention and contrastive spectral analysis

Discussion

Member takes

Implication

Key Points

Cite This Study

SCADET: A detection framework for AI-generated artwork integrating dynamic frequency attention and contrastive spectral analysis

Discussion

Member takes

Implication

Key Points

Cite This Study

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