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Can We Build a Monolithic Model for Fake Image Detection? SICA: Semantic-Induced Constrained Adaptation for Unified-Yet-Discriminative Artifact Feature Space Reconstruction
Bo Du, Xiaochen Ma, Xuekang Zhu +8
Fake Image Detection (FID), aiming at unified detection across four image forensic subdomains, is critical in real-world forensic scenarios. Compared with ensemble approaches, mono…
Revisiting Image Manipulation Localization under Realistic Manipulation Scenarios
Xuekang Zhu, Ji-Zhe Zhou, Kaiwen Feng +5
With the large models easing the labor-intensive manipulation process, image manipulations in today's real scenarios often entail a complex manipulation process, comprising a serie…
ForensicHub: A Unified Benchmark & Codebase for All-Domain Fake Image Detection and Localization
Bo Du, Xuekang Zhu, Xiaochen Ma +6
The field of Fake Image Detection and Localization (FIDL) is highly fragmented, encompassing four domains: deepfake detection (Deepfake), image manipulation detection and localizat…
TextSleuth: Towards Explainable Tampered Text Detection
Chenfan Qu, Jian Liu, Haoxing Chen +4
Recently, tampered text detection has attracted increasing attention due to its essential role in information security. Although existing methods can detect the tampered text regio…