UniShield: An Adaptive Multi-Agent Framework for Unified Forgery Image Detection and Localization

arXiv:2510.03161 · cs.CV, cs.AI · Submitted 2025-10-03 · Read on arXiv

cs.CV, cs.AI

Submitted: 2025-10-03

Updated: 2026-10-08

Code: https://github.com/Deep-Agent/R1-V

Terminology

• Benchmark — 11× in this paper · explained in 2 episodes
• Generalization — 10× in this paper · explained in 13 episodes
• Forgery Image Detection and Localization — 8× in this paper
• Interpretability — 7× in this paper · explained in 15 episodes
• F1 Score — 6× in this paper · explained in 3 episodes
• GRPO — 6× in this paper · explained in 6 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Reinforcement Learning — 5× in this paper · explained in 4 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• AUC — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Unified Framework — 3× in this paper · explained in 5 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Adaptability — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Federated Learning — 2× in this paper · explained in 14 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Image Manipulation Detection and Localization — 2× in this paper
• Multi-Agent Framework — 2× in this paper · explained in 3 episodes
• Reward Function — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Adversarial Training — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Group Relative Policy Optimization — 1× in this paper
• Group Relative Policy Optimization (GRPO) — 1× in this paper · explained in 5 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Multi-agent Collaboration — 1× in this paper · explained in 2 episodes
• Multimodal Inputs — 1× in this paper · explained in 2 episodes
• Multimodal Learning — 1× in this paper · explained in 2 episodes
• Non-IID Data — 1× in this paper · explained in 2 episodes
• Proximal Policy Optimization — 1× in this paper
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 4 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes

Sources

• Qwen2.5-VL Technical Report
• ShareGPT4V: Improving Large Multi-Modal Models with Better Captions
• BianQue: Balancing the Questioning and Suggestion Ability of Health LLMs with Multi-turn Health Conversations Polished by ChatGPT
• ForensicHub: A Unified Benchmark & Codebase for All-Domain Fake Image Detection and Localization
• UniForensics: Face Forgery Detection via General Facial Representation
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• FFAA: Multimodal Large Language Model based Explainable Open-World Face Forgery Analysis Assistant
• LEGION: Learning to Ground and Explain for Synthetic Image Detection
• MMCTAgent: Multi-modal Critical Thinking Agent Framework for Complex Visual Reasoning
• SepPrune: Structured Pruning for Efficient Deep Speech Separation
• MedCoT: Medical Chain of Thought via Hierarchical Expert
• IML-ViT: Benchmarking Image Manipulation Localization by Vision Transformer
• FakeFormer: Efficient Vulnerability-Driven Transformers for Generalisable Deepfake Detection
• TextSleuth: Towards Explainable Tampered Text Detection
• Spot the Fake: Large Multimodal Model-Based Synthetic Image Detection with Artifact Explanation
• Qwen-Image Technical Report
• MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning
• GPT-4 Technical Report
• AvatarShield: Visual Reinforcement Learning for Human-Centric Synthetic Video Detection
• A Sanity Check for AI-generated Image Detection

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