Fashion Matrix：只需对话即可编辑照片
Fashion Matrix: Editing Photos by Just Talking
AI总结：
Fashion Matrix利用大型语言模型与视觉基础模型协作，通过对话实现服装编辑，支持替换、换色等任务，展示了多模型协同的潜力。
摘要：
利用大型语言模型（LLMs）构建人工智能系统已在多个领域引起广泛关注。将LLMs扩展到时尚领域具有巨大的商业潜力，但由于时尚相关生成中复杂的语义交互，也面临固有挑战。为解决这一问题，我们开发了一个名为Fashion Matrix的层级式人工智能系统，专门用于通过对话编辑照片。该系统支持多种提示驱动的任务，包括服装或配饰的替换、重新着色、添加和移除。具体而言，Fashion Matrix以LLM作为基础支撑，并与用户进行迭代交互。它采用一系列语义分割模型（如Grounded-SAM、MattingAnything等）根据用户指令划定具体的编辑掩码。随后，利用视觉基础模型（如Stable Diffusion、ControlNet等）从文本提示和掩码生成编辑后的图像，从而促进时尚编辑过程的自动化。实验表明，Fashion Matrix在探索功能多样的预训练模型在时尚编辑领域的协作潜力方面表现出卓越能力。
英文摘要：
The utilization of Large Language Models (LLMs) for the construction of AI systems has garnered significant attention across diverse fields. The extension of LLMs to the domain of fashion holds substantial commercial potential but also inherent challenges due to the intricate semantic interactions in fashion-related generation. To address this issue, we developed a hierarchical AI system called Fashion Matrix dedicated to editing photos by just talking. This system facilitates diverse prompt-driven tasks, encompassing garment or accessory replacement, recoloring, addition, and removal. Specifically, Fashion Matrix employs LLM as its foundational support and engages in iterative interactions with users. It employs a range of Semantic Segmentation Models (e.g., Grounded-SAM, MattingAnything, etc.) to delineate the specific editing masks based on user instructions. Subsequently, Visual Foundation Models (e.g., Stable Diffusion, ControlNet, etc.) are leveraged to generate edited images from text prompts and masks, thereby facilitating the automation of fashion editing processes. Experiments demonstrate the outstanding ability of Fashion Matrix to explores the collaborative potential of functionally diverse pre-trained models in the domain of fashion editing.
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。
