合成图像有助于识别人造艺术品伪造
Johann Ostmeyer1, Ludovica Schaerf2, Pavel Buividovich1
1Department of Mathematical Sciences, University of Liverpool, Liverpool, United Kingdom.
PloS one
|February 14, 2024
概括
将人工智能生成的艺术品添加到训练数据中,可以显著提高对人造艺术品伪造的检测. 这种方法还有助于识别人工智能产生的假冒,特别是来自类似的人工智能模型的假冒.
科学领域:
- 艺术品的认证 艺术品的认证
- 人工智能的人工智能
- 计算机视觉 计算机视觉
背景情况:
- 人工智能 (AI) 在区分真实的艺术品和伪造品方面表现出高度准确性,并具有足够的培训数据.
- 已知艺术品伪造的有限数据集需要开发数据增强技术,以改进伪造检测.
研究的目的:
- 研究将合成艺术品纳入训练数据集的有效性,以提高基于AI的艺术品伪造检测的性能.
- 发布第一个专门用于艺术伪造检测的数据集,专注于文森特·高的画作.
主要方法:
- 训练了一个使用人工伪造和模仿的分类器,并增加了类似风格的AI生成的艺术品 (稳定扩散,StyleGAN).
- 对文森特·高,阿梅迪奥·莫迪利亚尼和拉斐尔的数据集进行了评估.
主要成果:
- 包括合成伪造品在内始终提高了人造伪造品的检测率.
- 使用合成伪造品的培训也使得人工智能生成的伪造品能够被检测出来,特别是当类似的人工智能模型生成的伪造品时.
结论:
- 合成艺术品生成是一种可行的增强方法,用于改进人工智能驱动的艺术品伪造检测系统.
- 这种方法提高了人工智能分类器对人类和人工智能生成的艺术伪造的稳定性.
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