Image Forgery Localization

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6 papers in the last four weeks, up 50% on the four weeks before. 0.1% of all new papers.

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Latest papers 46

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Order within Chaos: Capturing Intrinsic Energy Anomalies for AI-Manipulated Image Forgery Localization
Jun 1, 2026Yiming Wang, Baiqi Wu, Qingming Li +3Image Forgery Detection Digital Image Forensics
Zhejiang University, Hangzhou, China.
REVEAL: Reference-Grounded Reasoning for Multimodal Manipulation Detection
May 27, 2026Jun Zhou, Bingwen Hu, Yaxiong Wang +4Multimodal Grounding Image Forgery Detection
Multi-axis Analysis of Image Manipulation Localization
May 19, 2026Keanu Nichols, Divya Appapogu, Giscard Biamby +3Image Forgery Detection Domain Generalization
Boston University · University of California, Berkeley · Google +1
DocQT: Improving Document Forgery Localization Robustness via Diverse JPEG Quantization Tables
May 19, 2026Kylian Ronfleux-Corail, Guillaume Bernard, Mickaël Coustaty +1Image Corruption Robustness Image Forgery Detection
L3I · MAIF, Niort, France · L3i Laboratory, La Rochelle University, La Rochelle, France
OmniVL-Guard Pro: A Tool-Augmented Agent for Omnibus Vision-Language Forensics
May 16, 2026Jinjie Shen, Zheng Huang, Yuchen Zhang +7Tool Use in VLMs Image Forgery Detection
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China · Wuhan University, Wuhan, China · Xi’an Jiaotong University +2
Towards Generalized Image Manipulation Localization via Score-based Model
May 16, 2026Yunfei Wang, Bo Du, Zhe Yang +4Image Forgery Detection Image Forgery Localization
Sichuan University · Chengdu, China
Venus-DeFakerOne: Unified Fake Image Detection & Localization
May 13, 2026GuangJian TeamImage Forgery Detection Digital Image Forensics
Ant Group
FRAME: Forensic Routing and Adaptive Multi-path Evidence Fusion for Image Manipulation Detection
May 12, 2026Kaixiang Zhao, Tianrun Yu, Aoxu Zhang +3Image Forgery Detection Digital Image Forensics
1Brigham Young University · 2Rutgers University
EDGER: EDge-Guided with HEatmap Refinement for Generalizable Image Forgery Localization
May 12, 2026Minh-Khoa Le-Phan, Minh-Hoang Le, Minh-Triet Tran +1Image Forgery Detection Digital Image Forensics
University of Science - VNU-HCM, Ho Chi Minh City, Vietnam · Vietnam National University, Ho Chi Minh City, Vietnam
MFVLR: Multi-domain Fine-grained Vision-Language Reconstruction for Generalizable Diffusion Face Forgery Detection and Localization
May 11, 2026Yaning Zhang, Tianyi Wang, Zan Gao +3Vision-Language Models Image Forgery Detection
Faculty of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China · School of Computing, National University of Singapore, 21 Lower Kent Ridge Rd, 11907750, Singapore · Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China +2
EditSleuth: A Dataset of Grounded Reasoning Chains for Image-Edit Forensics
May 9, 2026Van-Loc Nguyen, AprilPyone MaungMaung, Minh-Triet Tran +1Image Forgery Detection Digital Image Forensics
University of Science, Vietnam National University Ho Chi Minh City · National Institute of Informatics
AEGIS: A Holistic Benchmark for Evaluating Forensic Analysis of AI-Generated Academic Images
Apr 30, 2026Bo Zhang, Tzu-Yen Ma, Zichen Tang +18Image Forgery Detection Digital Image Forensics
Beijing University of Posts and Telecommunications
Whether, Which, and Whose: Solving the Triple Challenge of Deepfake Proactive Forensics in Multi-Face Scenarios
Apr 29, 2026Lei Zhang, Zhiqing Guo, Dan Ma +2Digital Forensics Image Forgery Localization
School of Computer Science and Technology, Xinjiang University, Urumqi, 830017, China · Xinjiang Multimodal Intelligent Processing and Information Security Engineering Technology Research Center, Urumqi, 830017, China · College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China
DINOv3 Beats Specialized Detectors: A Simple Foundation Model Baseline for Image Forensics
Apr 17, 2026Jieming Yu, Qiuxiao Feng, Zhuohan Wang +1Image Forgery Detection Digital Image Forensics
The Hong Kong University of Science and Technology · Harvard University
The Courtroom Trial of Pixels: Robust Image Manipulation Localization via Adversarial Evidence and Reinforcement Learning Judgment
Apr 16, 2026Songlin Li, Zhiqing Guo, Dan Ma +2Image Forgery Detection Digital Image Forensics
School of Computer Science and Technology, Xinjiang University, Urumqi 830046, China
UniShield: An Adaptive Multi-Agent Framework for Unified Forgery Image Detection and Localization
Oct 3, 2025Qing Huang, Zhipei Xu, Xuanyu Zhang +2Image Forgery Detection Adaptive Model Routing
School of Electronic and Computer Engineering, Peking University · School of Future Technology, South China University of Technology · School of Electronic and Information Engineering, South China University of Technology +1

Jun 1, 2026, cs.CVJ/K move · Enter open · S save

Order within Chaos: Capturing Intrinsic Energy Anomalies for AI-Manipulated Image Forgery Localization

Yiming Wang, Baiqi Wu, Qingming Li, Jiahao Chen+2

Zhejiang University, Hangzhou, China.

Image Forgery Detection Digital Image Forensics Image Forgery Localization Anomaly Detection

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Recent advancements in generative AI have led to image editing models capable of producing realistic forgeries that evade traditional image forgery localization methods, as these approaches depend on physical noise absent in synthetic data. To address this challenge, we theoretically demonstrate that the diffusion process inherently suppresses local high-frequency variance, creating a statistical energy gap that is distinguishable from the natural entropy of optical imaging. Guided by this insight, we propose FLAME, a unified framework that utilizes a LAD map to capture these intrinsic anomalies, coupled with a parameter-efficient adapter for SAM to achieve precise, pixel-level forgery localization. Furthermore, to bridge the lag between forensic benchmarks and evolving generative models, we introduce EditStream, an automated pipeline for continuous, instruction-based training data synthesis. Extensive experiments demonstrate that FLAME establishes a new state-of-the-art, significantly outperforming previous methods on AI-generated forgery datasets while effectively generalizing to unseen generative architectures. Our code is available at https://github.com/phoenixnir/FLAME.

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