From the 1 of 7 linked papers with an AI index.
7 papers
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…
SWIFT: Sliding Window Reconstruction for Few-Shot Training-Free Generated Video Attribution
Chao Wang, Zijin Yang, Yaofei Wang +4
Recent advancements in video generation technologies have been significant, resulting in their widespread application across multiple domains. However, concerns have been mounting…
WMVLM: Evaluating Diffusion Model Image Watermarking via Vision-Language Models
Zijin Yang, Yu Sun, Kejiang Chen +4
Digital watermarking is essential for securing generated images from diffusion models. Accurate watermark evaluation is critical for algorithm development, yet existing methods hav…
SemBind: Binding Diffusion Watermarks to Semantics Against Black-Box Forgery Attacks
Xin Zhang, Zijin Yang, Kejiang Chen +3
Latent-based watermarks, integrated into the generation process of latent diffusion models (LDMs), simplify detection and attribution of generated images. However, recent black-box…
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…
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…