From the 2 of 18 linked papers with an AI index.
2 citations · 2 across the 7 of their papers we have counts for
8 papers · 1 filter
DNA: Dual-stage Native Attribution for Generated Image Source Tracing
Chao Wang, Kejiang Chen, Zijin Yang +4
The paper proposes DNA, a two‑stage framework that attributes generated images to their source models without additional training by first screening at the family level and then pi…
PTL-Diffusion: Manifold-Aware Diffusion with Periodic Terminal Laws
Danqi Zhuang, Jisui Huang, Xiaoyue Xi +4
Standard diffusion models typically use a single time-homogeneous Gaussian terminal distribution as the reference law for generation. While this choice is analytically convenient a…
AEDR: Training-Free AI-Generated Image Attribution via Autoencoder Double-Reconstruction
Chao Wang, Zijin Yang, Yaofei Wang +2
The rapid advancement of image-generation technologies has made it possible for anyone to create photorealistic images using generative models, raising significant security concern…
LiteUpdate: A Lightweight Framework for Updating AI-Generated Image Detectors
Jiajie Lu, Zhenkan Fu, Na Zhao +4
The rapid progress of generative AI has led to the emergence of new generative models, while existing detection methods struggle to keep pace, resulting in significant degradation…
T2SMark: Balancing Robustness and Diversity in Noise-as-Watermark for Diffusion Models
Jindong Yang, Han Fang, Weiming Zhang +2
Diffusion models have advanced rapidly in recent years, producing high-fidelity images while raising concerns about intellectual property protection and the misuse of generative AI…
Gaussian Shading++: Rethinking the Realistic Deployment Challenge of Performance-Lossless Image Watermark for Diffusion Models
Zijin Yang, Xin Zhang, Kejiang Chen +5
Ethical concerns surrounding copyright protection and inappropriate content generation pose challenges for the practical implementation of diffusion models. One effective solution…