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On the Coexistence and Ensembling of Watermarks
Conference paper

On the Coexistence and Ensembling of Watermarks

Aleksandar Petrov, Shruti Agarwal, Philip H. S Torr, Adel Bibi and John Collomosse
Advances in Neural Information Processing Systems 38: 39th Conference on Neural Information Processing Systems (NeurIPS 2025)
Advances in Neural Information Processing Systems, 38, Neural Information Processing Systems Foundation, Inc. (NeurIPS)
NeurIPS 2025: The Thirty-Ninth Annual Conference on Neural Information Processing Systems (San Diego, CA, USA, 02/12/2025–07/12/2025)
08/2026

Abstract

Computer Science - Artificial Intelligence Computer Science - Computer Vision and Pattern Recognition Computer Science - Computers and Society
Watermarking, the practice of embedding imperceptible information into media such as images, videos, audio, and text, is essential for intellectual property protection, content provenance and attribution. The growing complexity of digital ecosystems necessitates watermarks for different uses to be embedded in the same media. However, to detect and decode all watermarks, they need to coexist well with one another. We perform the first study of coexistence of deep image watermarking methods and, contrary to intuition, we find that various open-source watermarks can coexist with only minor impacts on image quality and decoding robustness. The coexistence of watermarks also opens the avenue for ensembling watermarking methods. We show how ensembling can increase the overall message capacity and enable new trade-offs between capacity, accuracy, robustness and image quality, without needing to retrain the base models.
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