This paper delves into the fascinating field of AI-generated art and explores the various deep neural network architectures and models that have been utilized to create it. From the classic convolutional networks to the cutting-edge diffusion models, we examine the key players in the field. We explain the general structures and working principles of these neural networks. Then, we showcase examples of milestones, starting with the dreamy landscapes of DeepDream and moving on to the most recent developments, including Stable Diffusion and DALL-E 2, which produce mesmerizing images. A detailed comparison of these models is provided, highlighting their strengths and limitations. Thus, we examine the remarkable progress that deep neural networks have made so far in a short period of time. With a unique blend of technical explanations and insights into the current state of AI-generated art, this paper exemplifies how art and computer science interact.

本文探讨了AI生成艺术领域，深入研究了用于创造艺术的各种深度神经网络体系结构和模型，包括传统的卷积网络和最前沿的扩散模型，并且实例展示了这一领域的关键成果，总结了这些模型的优缺点，探讨了目前深度神经网络在短时间内所取得的显著进展，展现了艺术与计算机科学的独特融合。

从笔触到像素：AI创作艺术中深度神经网络综述