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Signpost Watermarking: Joint Optimization for Visual Watermark Coexistence
Shruti Agarwal, Vishal Asnani, John Collomosse
We present a method for training imperceptible visual watermarks to coexist with other such watermarks. Recent work has shown that independently trained image watermarking models c…
FlowMark: Mask-Guided Video Watermarking
Vishal Asnani, Shruti Agarwal, John Collomosse
We present FlowMark, a video watermarking framework guided by automatically predicted object masks. In contrast to prior region-based approaches that require user-supplied mask gui…
TokenTrace: Multi-Concept Attribution through Watermarked Token Recovery
Li Zhang, Shruti Agarwal, John Collomosse +2
Generative AI models pose a significant challenge to intellectual property (IP), as they can replicate unique artistic styles and concepts without attribution. While watermarking o…
Latent Diffusion Unlearning: Protecting Against Unauthorized Personalization Through Trajectory Shifted Perturbations
Naresh Kumar Devulapally, Shruti Agarwal, Tejas Gokhale +1
Text-to-image diffusion models have demonstrated remarkable effectiveness in rapid and high-fidelity personalization, even when provided with only a few user images. However, the e…
Your Text Encoder Can Be An Object-Level Watermarking Controller
Naresh Kumar Devulapally, Mingzhen Huang, Vishal Asnani +3
Invisible watermarking of AI-generated images can help with copyright protection, enabling detection and identification of AI-generated media. In this work, we present a novel appr…
On the Coexistence and Ensembling of Watermarks
Aleksandar Petrov, Shruti Agarwal, Philip H. S. Torr +2
Watermarking, the practice of embedding imperceptible information into media such as images, videos, audio, and text, is essential for intellectual property protection, content pro…