133 citations · 188 across the 14 of their papers we have counts for
15 papers
On the Robustness of Watermarking for Autoregressive Image Generation
Andreas Müller, Denis Lukovnikov, Shingo Kodama +5
The proliferation of autoregressive (AR) image generators demands reliable detection and attribution of their outputs to mitigate misinformation, and to filter synthetic images fro…
ClusterMark: Towards Robust Watermarking for Autoregressive Image Generators with Visual Token Clustering
Denis Lukovnikov, Andreas Müller, Erwin Quiring +1
In-generation watermarking for latent diffusion models has recently shown high robustness in marking generated images for easier detection and attribution. However, its application…
Towards A Correct Usage of Cryptography in Semantic Watermarks for Diffusion Models
Jonas Thietke, Andreas Müller, Denis Lukovnikov +2
Semantic watermarking methods enable the direct integration of watermarks into the generation process of latent diffusion models by only modifying the initial latent noise. One lin…
Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models
Andreas Müller, Denis Lukovnikov, Jonas Thietke +2
Integrating watermarking into the generation process of latent diffusion models (LDMs) simplifies detection and attribution of generated content. Semantic watermarks, such as Tree-…
Layout-to-Image Generation with Localized Descriptions using ControlNet with Cross-Attention Control
Denis Lukovnikov, Asja Fischer
While text-to-image diffusion models can generate highquality images from textual descriptions, they generally lack fine-grained control over the visual composition of the generate…
AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error
Jonas Ricker, Denis Lukovnikov, Asja Fischer
With recent text-to-image models, anyone can generate deceptively realistic images with arbitrary contents, fueling the growing threat of visual disinformation. A key enabler for g…