使用局部自适应对抗颜色攻击抵御神经风格迁移的艺术品保护
Artwork Protection Against Neural Style Transfer Using Locally Adaptive Adversarial Color Attack
AI总结：
针对未经授权的神经风格迁移盗用艺术品问题，提出LAACA频率自适应扰动攻击与ACDM颜色差异度量，在保持视觉可接受性的同时显著降低风格化生成质量。
摘要：
神经风格迁移（NST）通过将一幅图像的风格与另一幅图像的内容相结合来生成新图像。然而，未经授权的NST可能会盗用艺术品，引发了对艺术家权利的担忧，并推动了主动保护方法的发展。我们提出局部自适应对抗颜色攻击（LAACA），使艺术家能够在公开发布前通过处理来保护其艺术品免受未经授权的风格迁移。通过深入研究人类视觉感知的复杂性以及不同频率成分的作用，我们的方法在图像中有策略地引入频率自适应扰动。这些扰动显著降低了NST的生成质量，同时在原始图像中保持可接受的视觉变化水平，确保潜在侵权者因其糟糕的NST生成质量而不愿使用受保护的艺术品。此外，现有指标在评估与颜色相关的任务（例如NST生成图像的质量）时往往忽视颜色保真度的重要性，而这在艺术作品语境中至关重要。为全面评估与颜色相关的任务，我们提出对抗颜色距离度量（ACDM），旨在量化图像在操作前后的颜色差异。实验结果证实，使用LAACA攻击NST会产生视觉上较差的风格迁移效果，并且ACDM能够有效衡量与颜色相关的任务。通过为艺术家提供保护其知识产权的工具，我们的工作缓解了艺术界因NST滥用而带来的社会技术挑战。
英文摘要：
Neural style transfer (NST) generates new images by combining the style of one image with the content of another. However, unauthorized NST can exploit artwork, raising concerns about artists' rights and motivating the development of proactive protection methods. We propose Locally Adaptive Adversarial Color Attack (LAACA), empowering artists to protect their artwork from unauthorized style transfer by processing before public release. By delving into the intricacies of human visual perception and the role of different frequency components, our method strategically introduces frequency-adaptive perturbations in the image. These perturbations significantly degrade the generation quality of NST while maintaining an acceptable level of visual change in the original image, ensuring that potential infringers are discouraged from using the protected artworks, because of its bad NST generation quality. Additionally, existing metrics often overlook the importance of color fidelity in evaluating color-mattered tasks, such as the quality of NST-generated images, which is crucial in the context of artistic works. To comprehensively assess the color-mattered tasks, we propose the Adversarial Color Distance Metric (ACDM), designed to quantify the color difference of images pre- and post-manipulations. Experimental results confirm that attacking NST using LAACA results in visually inferior style transfer, and the ACDM can efficiently measure color-mattered tasks. By providing artists with a tool to safeguard their intellectual property, our work relieves the socio-technical challenges posed by the misuse of NST in the art community.
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