April 24, 2023, 12:49 a.m. | Donghua Wang, Wen Yao, Tingsong Jiang, Weien Zhou, Lang Lin, Xiaoqian Chen

cs.CV updates on arXiv.org arxiv.org

Wide deployment of deep neural networks (DNNs) based applications (e.g.,
style transfer, cartoonish), stimulating the requirement of copyright
protection of such application's production. Although some traditional visible
copyright techniques are available, they would introduce undesired traces and
result in a poor user experience. In this paper, we propose a novel
plug-and-play invisible copyright protection method based on defensive
perturbation for DNN-based applications (i.e., style transfer). Rather than
apply the perturbation to attack the DNNs model, we explore the potential
utilization …

application applications apply arxiv copyright deployment dnn experience networks neural networks novel paper production project protection style transfer traces transfer

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