Procedural content generation (PCG) can be applied to a wide variety of tasks in games, from narratives, levels and sounds, to trees and weapons. A large amount of game content is comprised of graphical assets , such as clouds, buildings or vegetation, that do not require gameplay function considerations. There is also a breadth of literature examining the procedural generation of such elements for purposes outside of games. The body of research, focused on specific methods for generating specific assets, provides a narrow view of the available possibilities. Hence, it is difficult to have a clear picture of all approaches and possibilities, with no guide for interested parties to discover possible methods and approaches for their needs, and no facility to guide them through each technique or approach to map out the process of using them. Therefore, a systematic literature review has been conducted, yielding 239 accepted papers. This paper explores state-of-the-art approaches to graphical asset generation, examining research from a wide range of applications, inside and outside of games. Informed by the literature, a conceptual framework has been derived to address the aforementioned gaps.

中文翻译：

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图形游戏资产的智能生成：概念框架和最新技术系统回顾


程序化内容生成 （PCG） 可应用于游戏中的各种任务，从叙事、关卡和声音，到树木和武器。大量游戏内容由图形资产组成，例如云、建筑物或植被，这些资产不需要考虑游戏功能。还有大量文献研究了这些元素在游戏之外的程序生成。研究主体侧重于生成特定资产的特定方法，提供了可用可能性的狭隘视图。因此，很难清楚地了解所有方法和可能性，没有指导感兴趣的各方发现满足他们需求的可能方法和途径，也没有设施来指导他们通过每种技术或方法来规划使用它们的过程。因此，进行了系统的文献综述，产生了 239 篇被接受的论文。本白皮书探讨了图形资产生成的最先进方法，研究了来自游戏内外各种应用程序的研究。根据文献，已经衍生出一个概念框架来解决上述差距。