6 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…
Forging and Removing Latent-Noise Diffusion Watermarks Using a Single Image
Anubhav Jain, Yuya Kobayashi, Naoki Murata +6
Watermarking techniques are vital for protecting intellectual property and preventing fraudulent use of media. Most previous watermarking schemes designed for diffusion models embe…
FaceCloak: Learning to Protect Face Templates
Sudipta Banerjee, Anubhav Jain, Chinmay Hegde +1
Generative models can reconstruct face images from encoded representations (templates) bearing remarkable likeness to the original face, raising security and privacy concerns. We p…
Rethinking Negative Prompting for Concept Suppression: Unconditional Anchoring and Localized Guidance
Anubhav Jain, Yuya Kobayashi, Takashi Shibuya +4
Text-to-image diffusion models have rapidly transitioned from research prototypes to widely deployed tools. Along with their impressive capabilities, these models can also generate…
Classifier-Free Guidance inside the Attraction Basin May Cause Memorization
Anubhav Jain, Yuya Kobayashi, Takashi Shibuya +4
Diffusion models are prone to exactly reproduce images from the training data. This exact reproduction of the training data is concerning as it can lead to copyright infringement a…
Alpha-wolves and Alpha-mammals: Exploring Dictionary Attacks on Iris Recognition Systems
Sudipta Banerjee, Anubhav Jain, Zehua Jiang +3
A dictionary attack in a biometric system entails the use of a small number of strategically generated images or templates to successfully match with a large number of identities,…