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Auteurs principaux: Qiu, Jielin, Han, William, Zhao, Xuandong, Long, Shangbang, Faloutsos, Christos, Li, Lei
Format: Preprint
Publié: 2024
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Accès en ligne:https://arxiv.org/abs/2406.03728
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author Qiu, Jielin
Han, William
Zhao, Xuandong
Long, Shangbang
Faloutsos, Christos
Li, Lei
author_facet Qiu, Jielin
Han, William
Zhao, Xuandong
Long, Shangbang
Faloutsos, Christos
Li, Lei
contents With the development of large models, watermarks are increasingly employed to assert copyright, verify authenticity, or monitor content distribution. As applications become more multimodal, the utility of watermarking techniques becomes even more critical. The effectiveness and reliability of these watermarks largely depend on their robustness to various disturbances. However, the robustness of these watermarks in real-world scenarios, particularly under perturbations and corruption, is not well understood. To highlight the significance of robustness in watermarking techniques, our study evaluated the robustness of watermarked content generated by image and text generation models against common real-world image corruptions and text perturbations. Our results could pave the way for the development of more robust watermarking techniques in the future. Our project website can be found at \url{https://mmwatermark-robustness.github.io/}.
format Preprint
id arxiv_https___arxiv_org_abs_2406_03728
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Evaluating Durability: Benchmark Insights into Multimodal Watermarking
Qiu, Jielin
Han, William
Zhao, Xuandong
Long, Shangbang
Faloutsos, Christos
Li, Lei
Computer Vision and Pattern Recognition
With the development of large models, watermarks are increasingly employed to assert copyright, verify authenticity, or monitor content distribution. As applications become more multimodal, the utility of watermarking techniques becomes even more critical. The effectiveness and reliability of these watermarks largely depend on their robustness to various disturbances. However, the robustness of these watermarks in real-world scenarios, particularly under perturbations and corruption, is not well understood. To highlight the significance of robustness in watermarking techniques, our study evaluated the robustness of watermarked content generated by image and text generation models against common real-world image corruptions and text perturbations. Our results could pave the way for the development of more robust watermarking techniques in the future. Our project website can be found at \url{https://mmwatermark-robustness.github.io/}.
title Evaluating Durability: Benchmark Insights into Multimodal Watermarking
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2406.03728