🚨 Paper Alert 🚨
➡️Paper Title: PosterCopilot: Toward Layout Reasoning and Controllable Editing for Professional Graphic Design
🌟Few pointers from the paper
🎯Graphic design forms the cornerstone of modern visual communication, serving as a vital medium for promoting cultural and commercial events.
🎯 Recent advances have explored automating this process using Large Multimodal Models (LMMs), yet existing methods often produce geometrically inaccurate layouts and lack the iterative, layer-specific editing required in professional workflows.
🎯 To address these limitations, authors of this paper presented “PosterCopilot”, a framework that advances layout reasoning and controllable editing for professional graphic design.
🎯 Specifically, they introduced a progressive three-stage training strategy that equips LMMs with geometric understanding and aesthetic reasoning for layout design, consisting of Perturbed Supervised Fine-Tuning, Reinforcement Learning for Visual-Reality Alignment, and Reinforcement Learning from Aesthetic Feedback.
🎯 Furthermore, they developed a complete workflow that couples the trained LMM-based design model with generative models, enabling layer-controllable, iterative editing for precise element refinement while maintaining global visual consistency.
🎯 Extensive experiments demonstrate that PosterCopilot achieves geometrically accurate and aesthetically superior layouts, offering unprecedented controllability for professional iterative design.
🏢Organization: PRLab,
@NJU1902 ,
LibLib.ai, Institute of Automation, Chinese Academy of Sciences
🧙Paper Authors: Jiazhe Wei, Ken Li, Tianyu Lao,
@Haofan_Wang , Liang Wang, Caifeng Shan,
@scy994
📝 Read the Full Paper here:
arxiv.org/abs/2512.04082
🗂️ Project Page:
postercopilot.github.io/
🎥 Be sure to watch the attached Demo Video - Sound on 🔊🔊
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