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20242026
most citedTokenTrace: Multi-Concept Attribution through Watermarked Token Recovery

1 citations · 1 across the 3 of their papers we have counts for

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cs.CV2026

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…

cs.CV2026

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…

cs.CV20261 cited

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…

cs.CV2025

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…

cs.CV2024

FINEMATCH: Aspect-based Fine-grained Image and Text Mismatch Detection and Correction

Hang Hua, Jing Shi, Kushal Kafle +5

Recent progress in large-scale pre-training has led to the development of advanced vision-language models (VLMs) with remarkable proficiency in comprehending and generating multimo…

cs.CV2024

ProMark: Proactive Diffusion Watermarking for Causal Attribution

Vishal Asnani, John Collomosse, Tu Bui +2

Generative AI (GenAI) is transforming creative workflows through the capability to synthesize and manipulate images via high-level prompts. Yet creatives are not well supported to…