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English(EN) FlowTool: Controlling Tool Parameter in Image Retouching via Flow Matching

FlowTool 框架将图像修饰重构为流匹配问题

研究人员推出了一种新颖的图像修饰框架 FlowTool,它将该任务重构为流匹配问题。该方法直接对以输入图像和用户指令为条件的工具参数分布进行建模,利用了视觉语言模型骨干和扩散 Transformer。FlowTool 在多个基准测试中表现出优于现有的大型多模态语言模型和专用编辑代理的性能,同时在推理效率和内存使用方面也取得了显著改进。 AI

影响 这项研究为图像编辑提供了一种新方法,有望提高现有大型多模态语言模型的效率和性能。

排序理由 该条目描述了一篇详细介绍新颖图像修饰框架的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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FlowTool 框架将图像修饰重构为流匹配问题

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该条目描述了一篇详细介绍新颖图像修饰框架的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    FlowTool:通过流匹配控制图像修饰中的工具参数

    Tool-based image editing (image retouching) is commonly formulated with autoregressive multimodal large language models (MLLMs) that sequentially generate reasoning, tool selections, and parameter values. In this work, we present a novel approach to tool-based image editing by fr…