Research Paper#Image Manipulation Detection, AI-Generated Content, Benchmarking🔬 ResearchAnalyzed: Jan 3, 2026 18:55
NeXT-IMDL: A Benchmark for Robust Image Manipulation Detection
Published:Dec 29, 2025 11:09
•1 min read
•ArXiv
Analysis
This paper addresses the critical need for robust Image Manipulation Detection and Localization (IMDL) methods in the face of increasingly accessible AI-generated content. It highlights the limitations of current evaluation methods, which often overestimate model performance due to their simplified cross-dataset approach. The paper's significance lies in its introduction of NeXT-IMDL, a diagnostic benchmark designed to systematically probe the generalization capabilities of IMDL models across various dimensions of AI-generated manipulations. This is crucial because it moves beyond superficial evaluations and provides a more realistic assessment of model robustness in real-world scenarios.
Key Takeaways
- •Proposes NeXT-IMDL, a new benchmark for Image Manipulation Detection and Localization.
- •Focuses on evaluating generalization capabilities across different dimensions of AI-generated manipulations.
- •Highlights the limitations of current IMDL models in real-world scenarios.
- •Provides a diagnostic toolkit to advance the development of robust IMDL models.
Reference
“The paper reveals that existing IMDL models, while performing well in their original settings, exhibit systemic failures and significant performance degradation when evaluated under the designed protocols that simulate real-world generalization scenarios.”