arXiv Computer Vision
GIFTBench: Diagnosing Generalization in Image Forgery Localization and Informing Model Design
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arXiv Computer Vision
Aug 31
FUSED: Forensic-Semantic Mixture-of-Experts for AI Inpainting Detection and Localization
FUSED is a new framework that jointly detects and localizes AI-generated inpainting by combining low-level forensic cues with high-level semantic features through a sparsely-gated Mixture-of-Experts architecture. It predicts both an image-level manipulation score and a pixel-level mask of the inpainted region. On the OpenSDID cross-generator benchmark, FUSED outperforms existing methods, especially on unseen generators, and transfers effectively to the AutoSplice and CocoGlide benchmarks, doubling localization performance.
arXiv AI
6d ago
Geometric Inconsistency Localization in Multi-View Image Sets
The paper introduces DeformView, a wide‑baseline multi‑view dataset with pixel‑level annotations of geometric inconsistencies, and evaluates existing multi‑view consistency‑scoring methods, finding they transfer poorly to forensic localization tasks. To address this, the authors propose DEFECt3R, a lightweight learning‑based classifier that leverages cross‑view feature relationships and hard negative supervision to localize inconsistencies at the pixel level, achieving better performance and fewer false positives. Ablation studies confirm the importance of feature representations and correspondence quality for localization.
arXiv AI
Jul 21
Simple Domain Generalization for Strong Pixel-Level Image Tampering Detection in Modern VLMs
arXiv:2607. 18230v1 Announce Type: cross Abstract: Modern vision-language models (VLMs) have significantly improved image generation and editing capabilities, making pixel-level image tampering detection increasingly important yet challenging under cross-model and out-of-distribution shifts.
arXiv AI
Sep 10
Harnessing CLIP and DINO: An Uncertainty-Aware Cascaded Fusion Network for Generalizable Deepfake Image Detection
arXiv:2609.07670v1 Announce Type: cross Abstract: The growing realism and accessibility of manipulated and generated faces threaten the trustworthiness of digital media. To detect such forgeries, dee...
arXiv AI
3d ago
Forensic-Aware Continual Adaptation for Image Forgery Localization
arXiv:2609.38251v1 Announce Type: cross Abstract: The rapid evolution of image manipulation techniques has raised growing public security concerns. Existing Image Forgery Localization (IFL) methods c...
arXiv Computer Vision
4d ago
Less Supervision, Better Generalization: Weakly Supervised Fake Region Localization in Diffusion-Edited Images
arXiv:2609.36882v1 Announce Type: new Abstract: Localizing AI-edited regions is essential for interpretable forensic analysis, but remains challenging due to subtle and spatially distributed artifact...