用机器学习区分AI与人类创作的艺术作品，准确率超97%。
Detecting AI-generated Artwork
- 测试了多种机器学习模型，用图像特征识别艺术风格来源
- 二分类任务准确率达97.58%，多类分类达82.08%
- 对巴洛克、立体主义等复杂风格有效，适合版权与艺术鉴证场景
人工智能生成艺术的高效与高质量给人类艺术家带来了新的挑战，尤其是生成技术的进步使人们难以区分人类创作与AI生成的艺术作品。本研究探讨了多种机器学习（ML）与深度学习（DL）模型在辨别AI生成艺术与人类创作艺术方面的潜力。我们聚焦于巴洛克、立体主义和表现主义三种具有挑战性的艺术风格。测试的模型包括逻辑回归（LR）、支持向量机（SVM）、多层感知机（MLP）和卷积神经网络（CNN）。最佳实验结果在六类多分类任务中达到0.8208的准确率，在区分AI生成与人类生成艺术的二分类任务中取得0.9758的高准确率。
原文摘要 · Abstract (English)
The high efficiency and quality of artwork generated by Artificial Intelligence (AI) has created new concerns and challenges for human artists. In particular, recent improvements in generative AI have made it difficult for people to distinguish between human-generated and AI-generated art. In this research, we consider the potential utility of various types of Machine Learning (ML) and Deep Learning (DL) models in distinguishing AI-generated artwork from human-generated artwork. We focus on three challenging artistic styles, namely, baroque, cubism, and expressionism. The learning models we test are Logistic Regression (LR), Support Vector Machine (SVM), Multilayer Perceptron (MLP), and Convolutional Neural Network (CNN). Our best experimental results yield a multiclass accuracy of 0.8208 over six classes, and an impressive accuracy of 0.9758 for the binary classification problem of distinguishing AI-generated from human-generated art.
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