CLIP-Flow: A Universal Discriminator for AI-Generated Images Inspired by Anomaly Detection

Authors

Dong‐Ming Yan (ORCID: https://orcid.org/0000-0003-2209-2404)
Weize Quan (ORCID: https://orcid.org/0000-0003-0892-581X)
Tieru Wu (ORCID: https://orcid.org/0000-0003-3397-1885)
Kai Wang (ORCID: https://orcid.org/0000-0003-0053-3352)
Zhipeng Yuan (ORCID: https://orcid.org/0009-0005-4720-9498)

Institutions

Institut polytechnique de Grenoble (FR)
Centre National de la Recherche Scientifique (FR)
Jilin University (CN)
Chinese Academy of Sciences (CN)
Shandong Institute of Automation (CN)
GIPSA-Lab (FR)
Université Grenoble Alpes (FR)

Publication Details

Published: 2025-10-08
DOI: https://doi.org/10.1145/3746265.3759663
Primary Topic: Anomaly Detection Techniques and Applications
Type: article
Field-Weighted Citation Impact: 0.00

Funders

Agence Nationale de la Recherche

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article

CLIP-Flow: A Universal Discriminator for AI-Generated Images Inspired by Anomaly Detection

Dong‐Ming Yan, Weize Quan, Tieru Wu, Kai Wang et al.

Oct 8, 2025

Anomaly Detection Techniques and Applications

article

CLIP-Flow: A Universal Discriminator for AI-Generated Images Inspired by Anomaly Detection

Dong‐Ming Yan, Weize Quan, Tieru Wu, Kai Wang, Zhipeng Yuan

October 8, 2025article en

Abstract

No abstract available for this paper.

Institut polytechnique de Grenoble (FR), Centre National de la Recherche Scientifique (FR), Jilin University (CN), Chinese Academy of Sciences (CN), Shandong Institute of Automation (CN), GIPSA-Lab (FR), Université Grenoble Alpes (FR)

Agence Nationale de la Recherche

Openalex Percentile: Top 85%

Anomaly Detection Techniques and Applications

DOI Open Access PDF OpenAlex

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