With the development of the theory and technology of computer science, machine or computer painting is increasingly being explored in the creation of art. Machine-made works are referred to as artificial intelligence (AI) artworks. Early methods of AI artwork generation have been classified as non-photorealistic rendering (NPR) and, latterly, neural-style transfer methods have also been investigated. As technology advances, the variety of machine-generated artworks and the methods used to create them have proliferated. However, there is no unified and comprehensive system to classify and evaluate these works. To date, no work has generalised methods of creating AI artwork including learning-based methods for painting or drawing. Moreover, the taxonomy, evaluation and development of AI artwork methods face many challenges. This paper is motivated by these considerations. We first investigate current learning-based methods for making AI artworks and classify the methods according to art styles. Furthermore, we propose a consistent evaluation system for AI artworks and conduct a user study to evaluate the proposed system on different AI artworks. This evaluation system uses six criteria: beauty, color, texture, content detail, line and style. The user study demonstrates that the six-dimensional evaluation index is effective for different types of AI artworks.

中文翻译：

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基于学习的人工智能艺术作品：方法分类法和质量评估


随着计算机科学理论和技术的发展，机器或计算机绘画越来越多地被探索到艺术创作中。机器制造的作品被称为人工智能 （AI） 艺术品。早期的 AI 艺术品生成方法被归类为非照片级真实感渲染 （NPR），后来，还研究了神经风格的传输方法。随着技术的进步，机器生成的艺术品的种类和用于创作它们的方法激增。但是，没有一个统一和全面的系统来对这些作品进行分类和评估。迄今为止，还没有作品将创作 AI 艺术品的通用方法包括基于学习的绘画或素描方法。此外，AI 艺术品方法的分类、评估和开发面临许多挑战。本文的动机是这些考虑。我们首先研究了当前基于学习的 AI 艺术作品制作方法，并根据艺术风格对方法进行分类。此外，我们为 AI 艺术品提出了一个一致的评估系统，并进行了一项用户研究，以评估所提出的系统在不同 AI 艺术品上的应用。这个评价系统使用六个标准：美感、颜色、质感、内容细节、线条和风格。用户研究表明，六维评价指数对不同类型的 AI 艺术品都有效。