FlowTool: Controlling Tool Parameter in Image Retouching via Flow Matching
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 framing the task as a flow matching problem. We introduce FlowTool, a framework that directly models the distribution of high-quality tool parameters conditioned on the input image and user instruction using conditional rectified flow. FlowTool combines a vision-language model backbone for multimodal understanding with a Diffusion Transformer parameter generator that transforms Gaussian noise into an editing plan. W...
| Authors | Thanh-Long V. Le, Steven Walton, Seunghyun Yoon et al. |
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| Primary category | cs.CV |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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