首份实证研究揭示开源图像生成创作者的模型使用习惯。
Navigating the Open-Source Model Ecosystem: An Empirical Study of Creator Practices in Artistic Image Generation
- 构建600万张带元数据的图像数据集，追踪2.24万基础模型与15.4万LoRA使用情况。
- 发现创作者普遍组合使用多个开源模型，形成复杂创作流程。
- 研究成果可帮助优化生态可持续性，适合创作者与研究者参考。
开源强大图像生成模型催生了活跃的创作生态，创作者通过组合社区贡献的多种模型进行艺术创作，这与使用Midjourney等闭源工具形成鲜明对比。然而，关于这种新兴创作流程仍知之甚少。本文首次开展大规模实证研究，分析开源图像生成生态系统中创作者的模型使用行为。我们构建了一个包含600万张图像及其嵌入式生成元数据的新数据集——详细记录了创作过程中的模型使用和提示词信息。通过关联22.4K个基础模型和154K个LoRA模型的使用与图像产出，研究揭示了该生态系统的独特优势与内在挑战。这些发现为提升生态可持续性与创新能力提供了重要依据。此外，本研究公开数据集，为创作者提供实用参考，也为后续研究提供支持。
原文摘要 · Abstract (English)
The open-sourcing of powerful image generation models has created a vibrant ecosystem where creators curate and combine a vast array of community-contributed models. This practice stands in sharp contrast to using closed-source tools like Midjourney. Yet, little is known about these emerging creative workflows. To bridge this gap, this paper presents the first large-scale empirical study of creator model usage behavior within this open-source image generation ecosystem. We construct a novel dataset of 6 million images with their embedded generation metadata -- a detailed recipe of the creation process, including the models used and the prompts. By linking the usage of 22.4K base models and 154K LoRA models to the images, our findings underscore the ecosystem's unique strengths and its inherent obstacles. This provides valuable insights for making this ecosystem more sustainable and innovative. Moreover, we make our dataset publicly available, providing creators with practical references for producing better artworks and researchers to facilitate further studies.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。