用遗传改进自动优化图像生成流程，无需人工干预。
ComfyGI: Automatic Improvement of Image Generation Workflows
- 基于遗传改进技术自动调优图像生成工作流。
- 优化后图像在ImageReward评分中中位数提升约50%。
- 人类评估中90%偏好优化后的图像，适合懒人高效出图。
自动图像生成已不再仅受研究者关注，实践者也日益重视。然而，现有模型对参数设置敏感，自动优化方法常需人工参与。为此，我们提出ComfyGI，一种基于遗传改进技术的全新方法，可全自动优化图像生成工作流，无需人工干预。该方法显著提升了生成图像与描述的匹配度及视觉美感。性能方面，优化后工作流生成的图像在ImageReward评分中位数较初始工作流提升约50%。人类评估进一步验证其优势，参与者在约90%情况下更偏好ComfyGI优化后的图像。
原文摘要 · Abstract (English)
Automatic image generation is no longer just of interest to researchers, but also to practitioners. However, current models are sensitive to the settings used and automatic optimization methods often require human involvement. To bridge this gap, we introduce ComfyGI, a novel approach to automatically improve workflows for image generation without the need for human intervention driven by techniques from genetic improvement. This enables image generation with significantly higher quality in terms of the alignment with the given description and the perceived aesthetics. On the performance side, we find that overall, the images generated with an optimized workflow are about 50% better compared to the initial workflow in terms of the median ImageReward score. These already good results are even surpassed in our human evaluation, as the participants preferred the images improved by ComfyGI in around 90% of the cases.
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