6 papers
COCO-Inpaint: A Benchmark for Detecting and Localizing Inpainting-Based Image Manipulations
Haozhen Yan, Yan Hong, Jiahui Zhan +5
Recent advances in image manipulation have enabled highly photorealistic content generation, but also lowered the barrier to arbitrary editing, raising concerns about multimedia au…
Locate-Then-Examine: Grounded Region Reasoning Improves Detection of AI-Generated Images
Yikun Ji, Yan Hong, Bowen Deng +5
The rapid growth of AI-generated imagery has blurred the boundary between real and synthetic content, raising practical concerns for digital integrity. Vision-language models (VLMs…
Towards Source-Aware Object Swapping with Initial Noise Perturbation
Jiahui Zhan, Xianbing Sun, Xiangnan Zhu +4
Object swapping aims to replace a source object in a scene with a reference object while preserving object fidelity, scene fidelity, and object-scene harmony. Existing methods eith…
GAMMA: Generalizable Alignment via Multi-task and Manipulation-Augmented Training for AI-Generated Image Detection
Haozhen Yan, Yan Hong, Suning Lang +6
With generative models becoming increasingly sophisticated and diverse, detecting AI-generated images has become increasingly challenging. While existing AI-genereted Image detecto…
Towards Explainable Fake Image Detection with Multi-Modal Large Language Models
Yikun Ji, Yan Hong, Jiahui Zhan +6
Progress in image generation raises significant public security concerns. We argue that fake image detection should not operate as a "black box". Instead, an ideal approach must en…
Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs
Yikun Ji, Hong Yan, Jun Lan +5
The rapid advancement of image generation technologies intensifies the demand for interpretable and robust detection methods. Although existing approaches often attain high accurac…