Talk2Image：一种用于多轮图像生成与编辑的多智能体系统
Talk2Image: A Multi-Agent System for Multi-Turn Image Generation and Editing
AI总结：
针对多轮图像生成中单智能体易致意图偏移与编辑不连贯的问题，提出多智能体系统Talk2Image，通过意图解析、任务分解协同执行与反馈优化，实现与用户意图逐步对齐的一致图像编辑，显著优于现有基线。
摘要：
文本到图像生成任务推动了多样化媒体应用的显著进步，但大多数研究集中于单轮场景，在迭代式多轮创意任务中表现不佳。近期基于对话的系统试图弥补这一差距，但其单智能体、顺序式的范式常导致意图偏移和编辑不连贯。为了解决这些局限性，我们提出了Talk2Image，一种用于多轮对话场景中交互式图像生成与编辑的新型多智能体系统。该方法集成了三个关键组件：从对话历史中解析意图、跨专业智能体进行任务分解与协同执行，以及基于多视角评估机制的反馈驱动优化。Talk2Image实现了与用户意图的逐步对齐和一致的图像编辑。实验表明，在迭代式图像生成与编辑任务中，Talk2Image在可控性、连贯性和用户满意度方面均优于现有基线。
英文摘要：
Text-to-image generation tasks have driven remarkable advances in diverse media applications, yet most focus on single-turn scenarios and struggle with iterative, multi-turn creative tasks. Recent dialogue-based systems attempt to bridge this gap, but their single-agent, sequential paradigm often causes intention drift and incoherent edits. To address these limitations, we present Talk2Image, a novel multi-agent system for interactive image generation and editing in multi-turn dialogue scenarios. Our approach integrates three key components: intention parsing from dialogue history, task decomposition and collaborative execution across specialized agents, and feedback-driven refinement based on a multi-view evaluation mechanism. Talk2Image enables step-by-step alignment with user intention and consistent image editing. Experiments demonstrate that Talk2Image outperforms existing baselines in controllability, coherence, and user satisfaction across iterative image generation and editing tasks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
